Title of Invention	DEVICE FOR AUTOMATICALLY DETECTING SUBSTANTIALLY LINEAR SEISMIC EVENTS.
Abstract	There is disclosed a system for automatically detecting substantially linear seismic events in multiple element data, comprising, means for computing the complex trace envelope of traces of gather, means for sorting the gather by a first element line, a first element, a second element line, and a second element, means for transforming the sorted gather of complex trace envelopes defined by said means for computing and said means for sorting into a set of velocity stack trace envelopes, and means for picking events from the velocity stack trace envelopes.

Title of Invention

DEVICE FOR AUTOMATICALLY DETECTING SUBSTANTIALLY LINEAR SEISMIC EVENTS.

Abstract

There is disclosed a system for automatically detecting substantially linear seismic events in multiple element data, comprising, means for computing the complex trace envelope of traces of gather, means for sorting the gather by a first element line, a first element, a second element line, and a second element, means for transforming the sorted gather of complex trace envelopes defined by said means for computing and said means for sorting into a set of velocity stack trace envelopes, and means for picking events from the velocity stack trace envelopes.

Full Text	BACKGROUND OF THE INVENTION The invention relates to a device for automatically detecting substantially linear seismic events in the field of seismic data processing and specifically to methods for detecting arrival events, such as direct arrivals and refractions, and for detecting geometry and statics errors in seismic data. In seismic prospecting, signals are: generated at signal source locations by sources (e.g. air guns, dynamite, and vibrators) which travel through media, sometimes being refracted and reflected, and are received at receivers (e.g. hydrophones and geophones, a.k.a. pressure detectors and particle velocity detectors, respectively) The reflections-and-refraetions include information from which subsurface geology is determined. However, the process of acquiring the data is susceptible to error. For example, the amplitude of a particular shot from a particular source may not be as designed. A receiver may not be well-coupled (either to the recorder or the ground). Further problems in sources and receivers may be intermittent. As the number of sources and receivers increase, and as the volume of data increases with more and more dense 3D seismic activities, detection of such error becomes more and more difficult. Also, it is important to know the precise location of the sources and receivers, relative to one another. Again, as data volume has increased, this has become a particularly difficult problem, especially in marine environments, including ocean bottom cable and towed streamer applications. Even further, allowance must be made for variation in the elevation of receivers and sources, as well as variance in the depth to the sub-weathered layer, since the perceived depth of a particular event in a record is related to the time difference from the instant of the shot to the reception of the response to the shot. This is typically known as "statics" correction. In determining actual source or receiver location, and in performing statics corrections, typically, the first energy received by the receiver (a.k.a. the "first break") is used. For example, in some cases, the first break is the "direct arrival" (a signal received from the source which has not been reflected or refracted). In other cases, the first break is a refracted signal (e.g. in some ocean bottom cable situations). 1A Triangulation or least squares techniques use the first break to determine the relative position of shots and receivers. In the case of statics corrections, a decomposition algorithm is used, having the following general formula: ?t = ?xy + shot static error + receiver static error where ?xy is the position error of the shot and receiver, and where ?t is derived from refractors found in the data. See, Yilmaz, Seismic Data Processing, V.2, Ch 3, pp. 155-240, Society of Exploration Geophysicists (Tulsa, 1987). To determine the correct ?t function, however, the first break must be determined. This is riot a trivial task. In fact, it has proven to be very difficult. Currently, although attempts at automatic picking of the first break have been made, the picking still requires manual work, for most jobs. This manual work includes the time-consuming visual inspection of the data, since the automated processes are highly sensitive to noise. Further, the manual work may require a priori knowledge of the velocity, which is not always available. Visual inspection for good quality control defeats the very purpose of an automated system. Therefore, a reliable, automated system for detecting seismic events, such as the first break, is needed. Furthermore, techniques using first breaks; can only work with a single event per time axis. And, since the first break is the direct arrival for deep water cases only, traditional methods use only a few direct arrival traces for shallow water, disregarding all other traces where the direct arrival occurs at later time than the first break. A technique in which multiple events, especially one which could distinguish between the direct arrival and differing reflections is needed to provide greater flexibility and accuracy in the geometry correction and statics correction areas. Even further still, current geometry and statics correction processes use only first break information, making it more difficult to identify the type of error occurring. Therefore, a method is needed for detection and correction of geometry error and a method of detection and correction of statics error which the type of error is identifiable. Even further, current picking algorithms using correlation and stack/correlation techniques are subject to cycle skips, which is common, but very undesirable. Page 2 SUMMARY OF THE INVENTION It is an object of the present invention to address the above-identified needs. Therefore, according to one aspect of the invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the method comprising: band pass filtering the traces; computing the complex trace envelope of traces of the gather; filtering out a DC component of the traces; sorting the gather by a first element line, a first element, a second element line, a second element, and an offset bin, wherein a sorted gather of traces is defined; wherein said computing and said sorting define a sorted gather of complex trace envelopes; transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; wherein said traces are divergence corrected before said transforming and wherein said traces are positive bulk time shifted before said transforming; picking events from the velocity stack trace envelopes; determining statics error based on said picking; correcting said statics error; determining geometry error based on said picking; and correcting said geometry error. According to a further aspect of the invention, a dispersion filter is applied to the direct arrival data before said computing the complex envelope of traces gather. According to a further aspect of the invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the method comprising: computing the complex trace envelope of traces of the gather; sorting the gather by a first element line, a first element, a second element line, and a second element, wherein a sorted gather of traces is defined; Page 3 wherein said computing and said sorting define a sorted gather of complex trace envelopes; transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and picking events from the velocity stack trace envelopes. According to a further aspect of the invention, another method is provided, for correcting statics errors in a set of seismic data comprising: assembling a set of velocity stack trace envelopes; wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace; wherein the velocity stack trace envelopes include representations of multiple event arrivals; wherein some of the event arrivals represent the direct arrival and some represent events other than the direct arrival; wherein the velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event; comparing at least one event attribute of at least one of the multiple event arrivals to at least one event attribute of at least one other of the multiple event arrivals; and assigning a statics correction to a source-receiver, dependent upon the comparing. According to still a further aspect of the invention, a dispersion filter is applied to the direct arrival data before said computing the complex envelope of traces gather. According to still an another aspect of the present invention, a method is provided for discrimination between statics, geometry, source, and received problems, the method comprising: assembling a set of velocity stack trace envelopes; wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace; wherein the velocity stack trace envelopes include representations of multiple event arrivals; wherein some of the event arrivals represent the direct arrival and some represent events other than the direct arrival; Page 4 wherein the velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event; comparing at least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute; discriminating between error type, dependent upon the comparing. According to an even further aspect of the present invention, a method is provided for correcting geometry errors in a set of seismic data traces, the traces being related to a first element location and a second element location, one of the element locations being a shot location and the other of the element locations being a receiver location, the method comprising: assembling a set of velocity stack trace envelopes; picking a seismic event from the set of velocity stack trace envelopes; comparing a time delay between the first element location and the second clement location to a time delay threshold; and assigning a geometry correction to at least one of the element locations; dependent upon the comparing. Other aspects and embodiments will be apparent to a person of ordinary skill upon review of the following Brief Description of the Figures and Detailed Description of Example Embodiments of the Invention. Page 5 Accordingly the present invention provides a device for automatically detecting substantially linear seismic events in multiple element data, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the device comprising: a means for computing the complex trace envelope of traces of the gather; a means for sorting the gather by a first element line, a first element second element line, and a second element, wherein a sorted gather of traces is defined; wherein said means for computing and said means for sorting are adapted to define a sorted gather of complex trace envelopes; a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and a means for picking events from the velocity stack trace envelopes, wherein the different means as defined herein are computer hardware means comprising input devices, output devices, CPU, and memories, all adapted to carry out the program for the device. 5A BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS The present invention is better understood by reading the following description of nonlimitive embodiments with reference to the attached figures, which are briefly described as follows: FIGURE 1 demonstrates a method and system for automatically detecting substantially linear seismic events and for correcting geometry and statics errors in multiple element data. FIGURE 2 demonstrates a method and system for automatically detecting substantially linear seismic events in multiple element data. FIGURE 3 demonstrates a method and system for correcting statics errors in a set of seismic data. FIGURE 4 demonstrates a method and system for discriminating between statics, geometry, source and received problems. FIGURE 5 demonstrates a method and system for correcting geometry errors in a set of seismic data, FIGURE 6 demonstrates a method and system for automatically detecting substantially linear seismic events in multiple element data. FIGURE 7 demonstrates a method and system for assembling. FIGURE 8 demonstrates a method and system for correcting geometry errors in seismic data including substantially linear seismic events in multiple element data. FIGURE 9 demonstrates a method and system for automatically correcting statics errors in seismic data including substantially linear seismic events in multiple element data. FIGURE 10 demonstrates a device for automatically correcting statics errors in seismic data including substantially linear seismic events in multiple element data. It is to be noted, however, that the appended figures illustrate only typical embodiments of the invention, and are therefore, not to be considered a limitation of the scope of the invention, which includes other equally effective embodiments. 6 DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION According to one aspect of the present invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data. At least one element of the data comprises a shot location and at least one other element of the data comprises a receiver iocation. The data are gathered in a common element gather (e.g. common shot or common receiver), and the complex trace envelope of traces of the gather is computed (Figure 1C) (Figure 2A). Also, the gather is sorted by a first element line location (e.g. receiver line location, a first element location (e.g. receiver location), a second element line (e.g. a shot line location), and a second element (e.g. shot location), wherein a sorted gather of traces is defined (Figure 1E) (Figure 2C). In this example, the receiver is identified as the first element and the shot as the second element, but it will be understood that they are reversed in alternative embodiments of the invention. After sorting the traces and computing the complex trace envelopes, a gather of sorted trace envelopes is the result (Figure 1E). The method then transforms the sorted gather of trace envelopes into a set of velocity stack trace envelopes (Figure 1G) (Figure 2C), and events are picked from the velocity stack trace envelopes (Figure 1H). As used herein, velocity stack trace envelopes are the result of performing a tau-p transform (a.k.a. "slant stack") process on the sorted envelopes, or performing linear moveout with a single velocity (e.g. the water velocity in the case of bottom cable). The picking of the events from the velocity stack trace envelopes is then carried out by a number of processes, such as maxima detection (Figure 1H) (Figure 2D). The above method yields as many events ("event" meaning direct arrival, first refraction, second refraction, etc.) as are picked from the velocity stack traces. And, it should be noted that the picked events will have the following information associated with them if the tau-p transform process is used: time, amplitude, and velocity. Various additional steps are provided according to various embodiments of the invention. For example, in one embodiment, the transforming of the sorted gather of traces into a set of velocity stack trace envelopes (Figure 1G) comprises muting the direct arrival and the data in the traces after the direct arrival and applying a tau-p transform. While, according to an alternative embodiment, the transforming of the sorted gather of traces into a set of velocity stack trace envelopes comprises cluster maxima detection to detect events Page 7 other than the direct arrival. Further steps iinclude: divergence correcting the traces before the transforming (Figure 1F), band pass filtering the traces (using a source array dependent band pass filter for the detection of the direct arrival, and a band pass filter for all other events, as described in more detail below) (Figure 1A), filtering out a DC component of the traces (Figure 1D), applying a dispersion filter to the direct arrival data (Figure 1B) and positive bulk time shifting the traces before the transforming (Figure 1F). Regarding the band pass filtering, it has been found that the use of a specific type of filter for the direct arrival is particularly useful. As used herein, that filter is called a "source array dependent band pass filter," which is a high pass filter in which the cut frequencies are derived from the source array k filter for a given event apparent velocity. Regarding the dispersion filter, it has been found that when using traces with large shot to receiver distance (offset) the dispersive nature of the water propagated energy becomes evident. The wavelet containing the direct arrival is longer in time due to the fact that each frequency travels at a different velocity. A dispersion filter is applied to collapse the direct arrival energy to a shorter and more resolving wavelet. According to a further embodiment of the present invention the dispersion filter used is of the type: Phase (frequency) = frequency * offset / velocity (frequency) Of course, using other types of dispersion filters are envisioned as well. According to still a further embodiment of the present invention, the velocity stack traces are taken from a three dimensional survey, in which the offset bin information is preserved and used to build a cube of traces, referred to herein as a 3D velocity stack cube, plotted in, for example, shot line, shot, receiver line, receiver, offset bin, and time. Depending on which events are picked, such a cube represents the refractor structure and also the direct arrival horizon showing the geometry positions. If there are no geometry errors, the horizon will be flat. In the event there are geometry errors, the error will be seen in the cube (Figure IK). Further more, quality control issues will be detectable from the cube in that anomalies in the horizons will show various types of errors (e.g. misfires, in which all picks will have been shifted in the same amount, or direct arrival behavior which is different from the arrival of a refraction). Therefore, the velocity stack traces are used in accordance with a further aspect of the invention to determine geometry errors (Figure 1K). While according to Page 8 still a further aspect of the invention, the velocity stack traces are used to determine statics errors (Figure 11). According to an even further embodiment of the invention, a dispersion filter is applied to the direct arrival data (Figure 2A), a complex trace envelope of traces of the gather is computed (Figure 2B), the gather is sorted by a first element line, a first element, a second element line, and a second element, defining a sorted gather of traces and a sorted gather of complex trace envelopes (Figure 2C) and the sorted gather of complex trace envelopes is transformed into a set of velocity stack trace envelopes (Figure 2D). Events are then picked from the velocity stack trace envelopes (Figure 2E). According to an even further embodiment of the invention a complex trace envelope of traces of the gather is computed (Figure 6A), the gather is sorted by a first element line, a first element, a second element line, and a second element, defining a sorted gather of traces and a sorted gather of complex trace envelopes (Figure 6B) and the sorted gather of complex trace envelopes is transformed into a set of velocity stack trace envelopes (Figure 6C). Events are then picked from the velocity stack trace envelopes (Figure 6D). According to still a further embodiment of the invention, as explained in more detail below, events are associated with specific shot-receiver pairs, and various components of the events are analyzed (for example, by comparison to thresholds or other events) to determine geometry errors, static errors, and/or quality control (QC) (i.e., strength of source, miscalibration of receivers, etc.). In one specific example, guided correlation is used, as is traditional statics analysis. According to more specific examples of embodiments of the present invention, reformatted land header traces are inputted, represented by Sij(xys), Rkl(xys), A(X,t), where: i=a source line index, j=a source index, k=a receiver line index, l=a receiver index, xys=x,y coordinates + water depth, and A(X,t)=amplitude of the trace as a function of offset (X) and time (t). In a source process, the following steps are followed: Page 9 Event detection process: 1) Sort by Sij, receiver line to build a matrix having: {Sij,. Rkl, A(Xt)}, k=constant. 2) Compute the approximate water critical distance Xc at Sij according to any process known to those of skill in the art. 3) Compute the number of bins (m) and the maximum and minimum offsets of the bins (Xmin/max) according processes known to those of skill in the art. 4) Compute the average offset within the m offset bins to define Xm. 5) Extract a time window TX for each Sij, A(X,t), where TX=Tmax(Vw,X) , where Vw = water velocity and X is the offset. 6) Sort by m to build the matrix {Sij, Rkl, m, A(X,t)}. 7) Compute Rm(x,y,s)=average of Rl(x,y,s) for all traces in the offset bin m. 8) Duplicate the trace data, apply source array dependent high pass filter for the water arrival detection (one data set), apply regular band pass filter to the other data set. 9) Apply dispersion filter to the direct arrival data. 10) Compute complex trace envelope on both data sets. 11) Apply linear move out to data set one, at V=Vw and stack the m offset bin traces, A(X,t) to build {Sij, Rmk, As(Vw,t)}, where Vw = water velocity=Vd=direct arrival time. Notice l=receiver index is replaced by m=offset bin index. 12) Mute the direct arrival and all data later than the direct arrival to data set two 13) Slant stack (tau-p transform) the data set two, A(X,t) to build {Sij, m, As(Vs,t)}, where As(Vs,t) is the slant stack amplitude for each velocity and time index, or, if traces are noisy, use diversity slant stack. 14) Find the tau-p trace (As(Vs,t)) with the maximum amplitude (Asmax(t)) within the transform. That is Asmax(t) =MAX{As(Vs,t)}, and Vsmax=velocity associated to the Asmax(t). An alternative method is by cluster center maximum detection. Page 10 15) Write {Sij, RXmk, Xm, Asmax(t), Vr} including Vw data. Notice that Vr = Vsmax = refractor velocity and Asmax=amplitude of the velocity stack trace=amplitude of the refracted velocity=Ar. 16) Loop over m (offset bins). 17) Write {Sij, Rmk, Asmax(Xm,t), Vr}. 18) Loop over Rk (receiver line). 19) Write {Sij, Rmk, Asmax(Xm,t), Vr}. 20) Build cubes (Rmk(x,y), Asmax(t)} & {Rml(x,y), Vr}. 21) Pick cubes tr(Sij, Rmk, Asmax, Vr) by correlation and td(Sij,Rmk, Assd, Vw) finding maxima. Where tr=refractor time, td=direct arrival time. It will be understood by those of ordinary skill that the process described above is used in alternative embodiments as a receiver process, where R and S are interchanged. Event discrimination process: (Figure 4) From this type of data, various information is deduced. For example, many of the parameters written above are compared to threshold values, and/or to zero, to determine if an error exists in the data (Figure 4B). In one specific embodiment, a value TTHRSH is determined as a function of Rxkl and s. The TTHRSH value is compared against td and or tr, (arrival times for the direct arrival and a refraction, respectively). According to still a further embodiment, for QC purposes, the following matrix is calculated: TTHRSH ATHRSH VTHRSH td trAd Ar Vd Vr Sij R11 R21 A cube is built by calculating such a matrix for all Rkl's. Errors are detected by data in the cube that fall above or below a given threshold or are zero. For example, if there is a geometry error, most of the data points in a given matrix will be bad. If there is a statics error, on the other hand, the tr value will be bad, while other values are good. Further, if there Page 11 is a receiver line error, a constant error will appear for all the points on that given receiver line (e.g. amplitude = 0). Thus, according to another aspect of the invention, in a QC process, useful event attributes (as used herein, "event attributes" comprise: for example, td, tr, Ad, Ar, Vd, and Vr) are compared to threshold values and QC problems are flagged based on that comparison (Figure 4C). The type of QC error is determined from the pattern of nonconformance with the particular event attribute. In some embodiments, the error is plotted in the velocity stack cube (e.g. with a specific color designating a specific type of error) and the errors are plotted along with the xy contours. Next, all flagged Sij an Rkl trace gathers are plotted. According to a further embodiment a method for discriminating between statics, geometry, source and received problems is provided. This method is represented by Figure 4. A set of velocity stack trace envelopes is assembled, wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace and include representations of multiple event arrivals. (Figure 4A) Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival. The velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event. At least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute (Figure 4B); discriminating between error type dependant upon the comparing (Figure 4C). According to an alternative embodiment, rather than comparing the event attributes to threshold values, the event attributes for at least one trace are compared to the event attributes of at least one other trace. Errors are assigned to variances outside a predetermined level. Page 12 Geometry and statics corrections: (Figure 5) (Figure 3) According to an even further aspect of the invention, after assembling a set of velocity stack envelopes (Figure 5A) and picking a seismic event from that set of velocity stack trace envelopes (Figure 5B), the time delay between the first element location and the second element location is compared to a time delay threshold (Figure 5C). A geometry correction is then assigned dependent upon the comparison (Figure 5D). According to an even further aspect of the invention a set of velocity stack envelopes are assembled (Figure 3A); some event arrivals representing the direct arrival and some representing events other than the direct arrival. At least one event attribute of at least one of the multiple event arrivals is compared to at least one event attribute of at least one other of the multiple event arrivals (Figure 3B). A statics correction is then assigned to a source receiver (Figure 3C). According to an even further aspect of the invention, geometry corrections are provided by running triangulation or least squares location algorithms using the direct arrival attributes td tr(Sij(xy), Rmk(xy), Ad, Vd). A recomputed receiver location Sij(x',y') is then applied. According to an even further aspect of the invention, static corrections are provided by running conventional residual statics algorithms using the refractor arrival attributes td tr(Sij(x'y'), Rmk(xy), Ar, Vr). According to still an even further aspect of the invention a method for assembling, represented schematically in Figure 7, is provided. Compute the complex trace envelope of traces of a gather (Figure 7A), and sort the gather by a first clement line, a first element, a second element line, and a second element (Figure 7B). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Transform the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 7C), and pick events from the velocity stack trace envelopes (Figure 7D). According to an even further aspect of the invention a method for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors is provided. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. First, band pass filter the traces (Figure 1 A), compute the complex trace envelope of Page 13 traces of the gather (Figure 1C), sort the gather by a first element line, a first element, a second element line, a second element, and an offset bin (Figure 1E). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further, transform the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 1G). The traces are divergence corrected and positive bulk time shifted before transforming (Figure 1F). Pick events from the velocity stack trace envelopes (Figure 1H), determine statics error based on the picking (Figure 11), correct the statics error (Figure 1J), determine geometry error based on the picking (Figure 1K), and correct the geometry error (Figure 1L). According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented by Figure 1. Each block in Figure 1 represents a hardware/software module as would be known to one of ordinary skill in the art. For a common element gather of traces, at least one element of the data comprises a shot and at least one other element of the data comprises a receiver. A means for computing the complex trace envelope of traces of the gather is provided (Figure 1C). Also provided is a means for sorting the gather by a first element line, a first element, a second element line, and a second element; defining a sorted gather of traces (Figure 1E). The means for computing and the means for sorting define a sorted gather of complex trace envelopes (Figure 1E). There is also provided a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 1G) and for picking events from the velocity stack trace envelopes (Figure 1H). According to an even further aspect of the invention a means for transforming the sorted gather of traces into a set of velocity stack trace envelopes provides slant stack transforming of the gather of traces and maxima detecting (Figure 1G). Also embodied in the present invention is a means for transforming the sorted gather of traces into a set of velocity stack trace envelopes providing muting the direct arrival and the data in the traces after the direct arrival and applying a tau-p transform (Figure 1G). According to an even further aspect of the invention a means for picking is provided comprising cluster maxima detection (Figure 1H). Page 14 According to an even further aspect of the invention a means for sorting is provided for sorting the gather by offset bin (Figure 1E). According to still an even further aspect of the invention a means for divergence correcting the traces before the transforming is provided (Figure 1F). According to an even further aspect of the invention a means for band pass filtering the traces is provided (Figure 1 A). Another nonlimitive aspect of the invention includes source array dependent band pass filtering (Figure 1 A). According to an even further aspect of the inventions means for filtering out a DC component of the traces is provided (Figure 1D). According to still an even further aspect of the invention a means for positive bulk time shifting the traces before the transforming is provided (Figure 1F). According to an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data is provided before computing the complex trace envelope of traces of the gather (Figure 1B). According to an even further aspect of the invention a system for correcting statics errors in a set of seismic data is provided. Schematically this is represented by Figure 3. Each block in Figure 3 schematically represents a hardware/software module as would be known by one skilled in the art. A means for assembling a set of velocity stack trace envelopes is provided (Figure 3A). Also provided is a means for comparing at least one event attribute of at least one of the multiple event arrivals to at least one event attribute of at least one other of the multiple event arrivals (Figure 3B). Further, a means for assigning a statics correction to a source-receiver is provided (Figure 3C). The statics correction is dependent upon the comparing. The velocity stack trace envelopes have a particular shot and receiver location associated with each trace and the velocity stack trace envelopes include representations of multiple event arrivals. The velocity stack trace envelopes also include event attributes comprising: time, amplitude, and velocity information for each event. Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival. According to still an even further aspect of the invention a means for assembling. This is schematically represented by each block in Figure 7. Each block in Figure 7 represents a hardware/software module as would be known to one of ordinary skill in the art. A means for Page 15 computing the complex trace envelope of traces of a gather (Figure 7A) is provided, and for sorting the gather by a first element line, a first element, a second element line, and a second element (Figure 7B). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. A means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 7C), and picking events from the velocity stack trace envelopes is provided (Figure 7D). According to an even further aspect of the invention a system for discriminating between statics, geometry, source, and received problems is provided. This is schematically represented by Figure 4. Each block in Figure 4 represents a hardware/software module as would be known to one of ordinary skill in the art. Also provided is a means for assembling a set of velocity stack trace envelopes (Figure 4A). Further provided is a means for comparing at least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute (Figure 4B). Still further provided is a means for discriminating between error type, dependent upon the comparing, and a means for assembling a set of velocity stack trace envelopes (Figure 4C). The velocity stack trace envelopes have a particular shot and receiver location associated with each trace and the velocity stack trace envelopes include representations of multiple event arrivals. The velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event. Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival. According to an even further aspect of the invention a system for correcting geometry errors in a set of seismic data traces is provided. This is represented schematically by Figure 5. Each block in Figure 5 represents a hardware/software module as would be known to one of ordinary skill in the art. The traces are related to a first element location and a second element location, one of the element locations being a shot location and the other of the element locations being a receiver location. Further, a means for assembling a set of velocity stack trace envelopes including offset bin information is provided (Figure 5A). Also provided is a means for picking a seismic event from the set of velocity stack trace envelopes (Figure 5B), a means for comparing a time delay between the first element location and the second element location to a time delay threshold (Figure 5C), and a means for assigning a Page 16 geometry correction to at least one of the element locations; dependent upon the comparing (Figure 5D). According to an even further aspect of the invention a means for assembling is provided comprising assigning the traces to offset bins and applying moveout correction to the traces (Figure 5A). According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented in Figure 2. Each block in Figure 2 represents a hardware/software module as would be known to one of ordinary skill in the art. For a common gather of traces at least one element of the data comprises a shot and at least one other element of the data comprises a receiver. Also provided is a means for band pass filtering the traces, computing the complex trace envelope of traces of the gather (Figure 2A), filtering out a DC component of the traces and sorting the gather by a first element line, a first element, a second element line, a second element, and an offset bin. A sorted gather of traces is defined and computing and sorting define a sorted gather of complex trace envelopes (Figure 2B). Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 2C). The traces are divergence corrected and positive bulk time shifted before transforming. Also provided is a means for picking events from the velocity stack trace envelopes (Figure 2D). According to still an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data before said computing the complex trace envelope of traces of the gather is provided (Figure 1B). According to an even further aspect of the invention a system for automatically correcting geometry errors in seismic data including substantially linear seismic events in multiple element data is provided. This is represented schematically by Figure 8. Each block in Figure 8 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the trace (Figure 8A), computing the complex trace envelope of traces of the gather (Figure 8B), filtering out a DC component of the traces (Figure 8C), sorting the gather by a first element line, a first element, a second element line, a Page 17 second element, and an offset bin (Figure 8D). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 8F). The traces are divergence corrected and positive bulk time shifted before transforming (Figure 8E). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 8G), determining geometry error based on the picking (Figure 8H) and correcting the geometry error (Figure 81). According to an even further aspect of the invention a system for automatically correcting statics errors in seismic data including substantially linear seismic events in. multiple element data is provided. This is schematically represented by Figure 9. Each block in Figure 9 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the traces (Figure 9A), computing the complex trace envelope of traces of the gather (Figure 9B), filtering out a DC component of the traces (Figure 9C), sorting the gather by a first element line, a first element, a second element line, a second element (Figure 9D). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 9F). The traces are divergence corrected and positive bulk time shifted before the transforming (Figure 9E). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 9G), determining statics error based on the picking (Figure 1H) and correcting the statics error (Figure 91). 18 According to an even further aspect of the invention, a device for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented by a block diagram in Figure 10. At least one element of the data comprises a shot (Figure 10A) and at least one other element of the data comprises a receiver (Figure 10B), yielding a common element gather of traces (Figure 10C). The device comprises a means for computing the complex trace envelope of traces of the gather (Figure 10D) and a means for sorting the gather by a first element line, a first element, a second element line, and a second element (Figure 10E), wherein a sorted gather of traces is defined. The means for computing (Figure 10D) and the means for sorting (Figure 10E) define a sorted gather of complex trace envelopes (Figure 10F). The device also comprises a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 10G) and a means for picking events from the velocity stack trace envelopes (Figure 10H). The different means defined here are computer hardware comprising input devises, output devises, CPU, and memories, all adapted to carry out the program for the device. According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors is provided. This is schematically represented by Figure 1. Each block in Figure 1 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the traces (Figure 1 A), computing the complex trace envelope of traces of the gather (Figure 1C), sorting the gather by a first element line, a 18A first element, a second element line, a second element, and an offset bin (Figure 1E). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 1G). The said traces are divergence corrected and positive bulk time shifted before transforming (Figure 1F). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 1H), determining statics error based on the picking (Figure 11), correcting the statics error (Figure 1 J), determining geometry error based on the picking (Figure 1K), and correcting the geometry error (Figure 1L). According to still an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data before said computing the complex trace envelope of traces of the gather is provided (Figure 1B). Further embodiments and aspects of the invention will occur to those of skill in the art without departing from the spirit of the present invention. WE CLAIM: 1. A device for automatically detecting substantially linear seismic events in multiple element data, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the device comprising: a means for computing the complex trace envelope of traces of the gather; a means for sorting the gather by a first element line, a first element, a second element line, and a second element, wherein a sorted gather of traces is defined; wherein said means for computing and said means for sorting are adapted to define a sorted gather of complex trace envelopes; a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and a means for picking events from the velocity stack trace envelopes, wherein the different means as defined herein are computer hardware means comprising input devices, output devices, CPU, and memories, all adapted to carry out the program for the device. 2. A device as claimed in claim 1, wherein said means for transforming the sorted gather of traces into a set of velocity stack trace envelopes comprises: a means for slant stack transforming of the gather of traces; and a means for maxima detecting. 3. A device as claimed in claim 1, wherein said means for transforming the sorted gather of traces into a set of velocity stack trace envelopes comprises a means for muting the direct arrival and the data in the traces after the direct arrival and applying a tau-p transform. 20 4. A device as claimed in claim 1, wherein said means for picking comprises cluster maxima detection. 5. A device as claimed in claim 1, wherein said means for transforming the sorted gather of traces into a set of velocity stack trace envelopes comprises a means for applying a tau-p transform. 6. A device as claimed in claim 1, wherein said means for sorting comprises a means for sorting the gather by offset bin. 7. A device as claimed in claim 1, wherein said means for transforming comprises a means for divergence correcting the traces beforehand. 8. A device as claimed in claim 1, wherein said means for computing comprises a means for band pass filtering the traces beforehand. 9. A device as claimed in claim 8, wherein said means for band pass filtering comprises a means for source array dependent band pass filtering. 10. A device as claimed in claim 1, wherein said means for computing comprises a means for filtering out a DC component of the traces afterwards. 11. A device as claimed in claim 1, wherein said means for transforming comprises a means for positive bulk time shifting the traces beforehand. 12. A device as claimed in claim 1, wherein said means for computing the complex trace envelope of traces of the gather comprises a means for applying a dispersion filter to the direct arrival data beforehand. 21 13. A device for automatically detecting substantially linear seismic events, substantially as herein described, particularly with reference to and as illustrated in the accompanying drawings. There is disclosed a system for automatically detecting substantially linear seismic events in multiple element data, comprising, means for computing the complex trace envelope of traces of gather, means for sorting the gather by a first element line, a first element, a second element line, and a second element, means for transforming the sorted gather of complex trace envelopes defined by said means for computing and said means for sorting into a set of velocity stack trace envelopes, and means for picking events from the velocity stack trace envelopes.

Full Text

BACKGROUND OF THE INVENTION
The invention relates to a device for automatically detecting substantially linear seismic events in the field of seismic data processing and specifically to methods for detecting arrival events, such as direct arrivals and refractions, and for detecting geometry and statics errors in seismic data.
In seismic prospecting, signals are: generated at signal source locations by sources (e.g. air guns, dynamite, and vibrators) which travel through media, sometimes being refracted and reflected, and are received at receivers (e.g. hydrophones and geophones, a.k.a. pressure detectors and particle velocity detectors, respectively) The reflections-and-refraetions include information from which subsurface geology is determined. However, the process of acquiring the data is susceptible to error.
For example, the amplitude of a particular shot from a particular source may not be as designed. A receiver may not be well-coupled (either to the recorder or the ground). Further problems in sources and receivers may be intermittent. As the number of sources and receivers increase, and as the volume of data increases with more and more dense 3D seismic activities, detection of such error becomes more and more difficult.
Also, it is important to know the precise location of the sources and receivers, relative to one another. Again, as data volume has increased, this has become a particularly difficult problem, especially in marine environments, including ocean bottom cable and towed streamer applications.
Even further, allowance must be made for variation in the elevation of receivers and sources, as well as variance in the depth to the sub-weathered layer, since the perceived depth of a particular event in a record is related to the time difference from the instant of the shot to the reception of the response to the shot. This is typically known as "statics" correction.
In determining actual source or receiver location, and in performing statics corrections, typically, the first energy received by the receiver (a.k.a. the "first break") is used. For example, in some cases, the first break is the "direct arrival" (a signal received from the source which has not been reflected or refracted). In other cases, the first break is a refracted signal (e.g. in some ocean bottom cable situations).
1A

Triangulation or least squares techniques use the first break to determine the relative position of shots and receivers. In the case of statics corrections, a decomposition algorithm is used, having the following general formula:
?t = ?xy + shot static error + receiver static error where ?xy is the position error of the shot and receiver, and where ?t is derived from refractors found in the data. See, Yilmaz, Seismic Data Processing, V.2, Ch 3, pp. 155-240, Society of Exploration Geophysicists (Tulsa, 1987).
To determine the correct ?t function, however, the first break must be determined. This is riot a trivial task. In fact, it has proven to be very difficult.
Currently, although attempts at automatic picking of the first break have been made, the picking still requires manual work, for most jobs. This manual work includes the time-consuming visual inspection of the data, since the automated processes are highly sensitive to noise. Further, the manual work may require a priori knowledge of the velocity, which is not always available. Visual inspection for good quality control defeats the very purpose of an automated system. Therefore, a reliable, automated system for detecting seismic events, such as the first break, is needed.
Furthermore, techniques using first breaks; can only work with a single event per time axis. And, since the first break is the direct arrival for deep water cases only, traditional methods use only a few direct arrival traces for shallow water, disregarding all other traces where the direct arrival occurs at later time than the first break. A technique in which multiple events, especially one which could distinguish between the direct arrival and differing reflections is needed to provide greater flexibility and accuracy in the geometry correction and statics correction areas.
Even further still, current geometry and statics correction processes use only first break information, making it more difficult to identify the type of error occurring. Therefore, a method is needed for detection and correction of geometry error and a method of detection and correction of statics error which the type of error is identifiable. Even further, current picking algorithms using correlation and stack/correlation techniques are subject to cycle skips, which is common, but very undesirable.
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SUMMARY OF THE INVENTION
It is an object of the present invention to address the above-identified needs. Therefore, according to one aspect of the invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the method comprising:
band pass filtering the traces;
computing the complex trace envelope of traces of the gather;
filtering out a DC component of the traces;
sorting the gather by a first element line, a first element, a second element line, a second element, and an offset bin, wherein a sorted gather of traces is defined;
wherein said computing and said sorting define a sorted gather of complex trace envelopes;
transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; wherein said traces are divergence corrected before said transforming and wherein said traces are positive bulk time shifted before said transforming;
picking events from the velocity stack trace envelopes;
determining statics error based on said picking;
correcting said statics error;
determining geometry error based on said picking; and
correcting said geometry error.
According to a further aspect of the invention, a dispersion filter is applied to the direct arrival data before said computing the complex envelope of traces gather.
According to a further aspect of the invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the method comprising:
computing the complex trace envelope of traces of the gather;
sorting the gather by a first element line, a first element, a second element line, and a second element, wherein a sorted gather of traces is defined;
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wherein said computing and said sorting define a sorted gather of complex trace envelopes;
transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and
picking events from the velocity stack trace envelopes.
According to a further aspect of the invention, another method is provided, for correcting statics errors in a set of seismic data comprising:
assembling a set of velocity stack trace envelopes;
wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace;
wherein the velocity stack trace envelopes include representations of multiple event arrivals;
wherein some of the event arrivals represent the direct arrival and some represent events other than the direct arrival;
wherein the velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event;
comparing at least one event attribute of at least one of the multiple event arrivals to at least one event attribute of at least one other of the multiple event arrivals; and
assigning a statics correction to a source-receiver, dependent upon the comparing.
According to still a further aspect of the invention, a dispersion filter is applied to the direct arrival data before said computing the complex envelope of traces gather.
According to still an another aspect of the present invention, a method is provided for discrimination between statics, geometry, source, and received problems, the method comprising:
assembling a set of velocity stack trace envelopes;
wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace;
wherein the velocity stack trace envelopes include representations of multiple event arrivals;
wherein some of the event arrivals represent the direct arrival and some represent events other than the direct arrival;
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wherein the velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event;
comparing at least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute;
discriminating between error type, dependent upon the comparing.
According to an even further aspect of the present invention, a method is provided for correcting geometry errors in a set of seismic data traces, the traces being related to a first element location and a second element location, one of the element locations being a shot location and the other of the element locations being a receiver location, the method comprising:
assembling a set of velocity stack trace envelopes;
picking a seismic event from the set of velocity stack trace envelopes;
comparing a time delay between the first element location and the second clement location to a time delay threshold; and
assigning a geometry correction to at least one of the element locations; dependent upon the comparing.
Other aspects and embodiments will be apparent to a person of ordinary skill upon review of the following Brief Description of the Figures and Detailed Description of Example Embodiments of the Invention.
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Accordingly the present invention provides a device for automatically detecting substantially linear seismic events in multiple element data, wherein at least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces, the device comprising:
a means for computing the complex trace envelope of traces of the gather;
a means for sorting the gather by a first element line, a first element second element line, and a second element, wherein a sorted gather of traces is defined;
wherein said means for computing and said means for sorting are adapted to define a sorted gather of complex trace envelopes;
a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and
a means for picking events from the velocity stack trace envelopes,
wherein the different means as defined herein are computer hardware means comprising input devices, output devices, CPU, and memories, all adapted to carry out the program for the device.
5A

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The present invention is better understood by reading the following description of nonlimitive embodiments with reference to the attached figures, which are briefly described as follows:
FIGURE 1 demonstrates a method and system for automatically detecting
substantially linear seismic events and for correcting geometry and statics errors in
multiple element data.
FIGURE 2 demonstrates a method and system for automatically detecting
substantially linear seismic events in multiple element data.
FIGURE 3 demonstrates a method and system for correcting statics errors in a set of
seismic data.
FIGURE 4 demonstrates a method and system for discriminating between statics,
geometry, source and received problems.
FIGURE 5 demonstrates a method and system for correcting geometry errors in a set
of seismic data,
FIGURE 6 demonstrates a method and system for automatically detecting
substantially linear seismic events in multiple element data.
FIGURE 7 demonstrates a method and system for assembling.
FIGURE 8 demonstrates a method and system for correcting geometry errors in
seismic data including substantially linear seismic events in multiple element data.
FIGURE 9 demonstrates a method and system for automatically correcting statics
errors in seismic data including substantially linear seismic events in multiple element
data.
FIGURE 10 demonstrates a device for automatically correcting statics errors in seismic data including substantially linear seismic events in multiple element data.
It is to be noted, however, that the appended figures illustrate only typical embodiments of the invention, and are therefore, not to be considered a limitation of the scope of the invention, which includes other equally effective embodiments.
6

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION
According to one aspect of the present invention, a method is provided for automatically detecting substantially linear seismic events in multiple element data. At least one element of the data comprises a shot location and at least one other element of the data comprises a receiver iocation. The data are gathered in a common element gather (e.g. common shot or common receiver), and the complex trace envelope of traces of the gather is computed (Figure 1C) (Figure 2A). Also, the gather is sorted by a first element line location (e.g. receiver line location, a first element location (e.g. receiver location), a second element line (e.g. a shot line location), and a second element (e.g. shot location), wherein a sorted gather of traces is defined (Figure 1E) (Figure 2C). In this example, the receiver is identified as the first element and the shot as the second element, but it will be understood that they are reversed in alternative embodiments of the invention.
After sorting the traces and computing the complex trace envelopes, a gather of sorted trace envelopes is the result (Figure 1E). The method then transforms the sorted gather of trace envelopes into a set of velocity stack trace envelopes (Figure 1G) (Figure 2C), and events are picked from the velocity stack trace envelopes (Figure 1H).
As used herein, velocity stack trace envelopes are the result of performing a tau-p transform (a.k.a. "slant stack") process on the sorted envelopes, or performing linear moveout with a single velocity (e.g. the water velocity in the case of bottom cable). The picking of the events from the velocity stack trace envelopes is then carried out by a number of processes, such as maxima detection (Figure 1H) (Figure 2D).
The above method yields as many events ("event" meaning direct arrival, first refraction, second refraction, etc.) as are picked from the velocity stack traces. And, it should be noted that the picked events will have the following information associated with them if the tau-p transform process is used: time, amplitude, and velocity.
Various additional steps are provided according to various embodiments of the invention. For example, in one embodiment, the transforming of the sorted gather of traces into a set of velocity stack trace envelopes (Figure 1G) comprises muting the direct arrival and the data in the traces after the direct arrival and applying a tau-p transform. While, according to an alternative embodiment, the transforming of the sorted gather of traces into a set of velocity stack trace envelopes comprises cluster maxima detection to detect events
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other than the direct arrival. Further steps iinclude: divergence correcting the traces before the transforming (Figure 1F), band pass filtering the traces (using a source array dependent band pass filter for the detection of the direct arrival, and a band pass filter for all other events, as described in more detail below) (Figure 1A), filtering out a DC component of the traces (Figure 1D), applying a dispersion filter to the direct arrival data (Figure 1B) and positive bulk time shifting the traces before the transforming (Figure 1F).
Regarding the band pass filtering, it has been found that the use of a specific type of filter for the direct arrival is particularly useful. As used herein, that filter is called a "source array dependent band pass filter," which is a high pass filter in which the cut frequencies are derived from the source array k filter for a given event apparent velocity.
Regarding the dispersion filter, it has been found that when using traces with large shot to receiver distance (offset) the dispersive nature of the water propagated energy becomes evident. The wavelet containing the direct arrival is longer in time due to the fact that each frequency travels at a different velocity. A dispersion filter is applied to collapse the direct arrival energy to a shorter and more resolving wavelet.
According to a further embodiment of the present invention the dispersion filter used is of the type:
Phase (frequency) = frequency * offset / velocity (frequency) Of course, using other types of dispersion filters are envisioned as well.
According to still a further embodiment of the present invention, the velocity stack traces are taken from a three dimensional survey, in which the offset bin information is preserved and used to build a cube of traces, referred to herein as a 3D velocity stack cube, plotted in, for example, shot line, shot, receiver line, receiver, offset bin, and time. Depending on which events are picked, such a cube represents the refractor structure and also the direct arrival horizon showing the geometry positions. If there are no geometry errors, the horizon will be flat. In the event there are geometry errors, the error will be seen in the cube (Figure IK). Further more, quality control issues will be detectable from the cube in that anomalies in the horizons will show various types of errors (e.g. misfires, in which all picks will have been shifted in the same amount, or direct arrival behavior which is different from the arrival of a refraction). Therefore, the velocity stack traces are used in accordance with a further aspect of the invention to determine geometry errors (Figure 1K). While according to
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still a further aspect of the invention, the velocity stack traces are used to determine statics errors (Figure 11).
According to an even further embodiment of the invention, a dispersion filter is applied to the direct arrival data (Figure 2A), a complex trace envelope of traces of the gather is computed (Figure 2B), the gather is sorted by a first element line, a first element, a second element line, and a second element, defining a sorted gather of traces and a sorted gather of complex trace envelopes (Figure 2C) and the sorted gather of complex trace envelopes is transformed into a set of velocity stack trace envelopes (Figure 2D). Events are then picked from the velocity stack trace envelopes (Figure 2E).
According to an even further embodiment of the invention a complex trace envelope of traces of the gather is computed (Figure 6A), the gather is sorted by a first element line, a first element, a second element line, and a second element, defining a sorted gather of traces and a sorted gather of complex trace envelopes (Figure 6B) and the sorted gather of complex trace envelopes is transformed into a set of velocity stack trace envelopes (Figure 6C). Events are then picked from the velocity stack trace envelopes (Figure 6D).
According to still a further embodiment of the invention, as explained in more detail below, events are associated with specific shot-receiver pairs, and various components of the events are analyzed (for example, by comparison to thresholds or other events) to determine geometry errors, static errors, and/or quality control (QC) (i.e., strength of source, miscalibration of receivers, etc.). In one specific example, guided correlation is used, as is traditional statics analysis.
According to more specific examples of embodiments of the present invention, reformatted land header traces are inputted, represented by Sij(xys), Rkl(xys), A(X,t), where:
i=a source line index,
j=a source index,
k=a receiver line index,
l=a receiver index,
xys=x,y coordinates + water depth, and
A(X,t)=amplitude of the trace as a function of offset (X) and time (t). In a source process, the following steps are followed:
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Event detection process:
1) Sort by Sij, receiver line to build a matrix having: {Sij,. Rkl, A(Xt)}, k=constant.
2) Compute the approximate water critical distance Xc at Sij according to any process known to those of skill in the art.
3) Compute the number of bins (m) and the maximum and minimum offsets of the bins (Xmin/max) according processes known to those of skill in the art.
4) Compute the average offset within the m offset bins to define Xm.
5) Extract a time window TX for each Sij, A(X,t), where TX=Tmax(Vw,X) , where Vw = water velocity and X is the offset.
6) Sort by m to build the matrix {Sij, Rkl, m, A(X,t)}.
7) Compute Rm(x,y,s)=average of Rl(x,y,s) for all traces in the offset bin m.

8) Duplicate the trace data, apply source array dependent high pass filter for the water arrival detection (one data set), apply regular band pass filter to the other data set.
9) Apply dispersion filter to the direct arrival data.
10) Compute complex trace envelope on both data sets.

11) Apply linear move out to data set one, at V=Vw and stack the m offset bin traces, A(X,t) to build {Sij, Rmk, As(Vw,t)}, where Vw = water velocity=Vd=direct arrival time. Notice l=receiver index is replaced by m=offset bin index.
12) Mute the direct arrival and all data later than the direct arrival to data set two
13) Slant stack (tau-p transform) the data set two, A(X,t) to build {Sij, m, As(Vs,t)}, where As(Vs,t) is the slant stack amplitude for each velocity and time index, or, if traces are noisy, use diversity slant stack.
14) Find the tau-p trace (As(Vs,t)) with the maximum amplitude (Asmax(t)) within the transform. That is Asmax(t) =MAX{As(Vs,t)}, and Vsmax=velocity associated to the Asmax(t). An alternative method is by cluster center maximum detection.
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15) Write {Sij, RXmk, Xm, Asmax(t), Vr} including Vw data. Notice that Vr = Vsmax = refractor velocity and Asmax=amplitude of the velocity stack trace=amplitude of the refracted velocity=Ar.
16) Loop over m (offset bins).
17) Write {Sij, Rmk, Asmax(Xm,t), Vr}.
18) Loop over Rk (receiver line).
19) Write {Sij, Rmk, Asmax(Xm,t), Vr}.
20) Build cubes (Rmk(x,y), Asmax(t)} & {Rml(x,y), Vr}.
21) Pick cubes tr(Sij, Rmk, Asmax, Vr) by correlation and td(Sij,Rmk, Assd, Vw) finding maxima. Where tr=refractor time, td=direct arrival time.
It will be understood by those of ordinary skill that the process described above is used in alternative embodiments as a receiver process, where R and S are interchanged.
Event discrimination process: (Figure 4)
From this type of data, various information is deduced. For example, many of the parameters written above are compared to threshold values, and/or to zero, to determine if an error exists in the data (Figure 4B). In one specific embodiment, a value TTHRSH is determined as a function of Rxkl and s. The TTHRSH value is compared against td and or tr, (arrival times for the direct arrival and a refraction, respectively).
According to still a further embodiment, for QC purposes, the following matrix is calculated:
TTHRSH ATHRSH VTHRSH
td trAd Ar Vd Vr
Sij R11 R21
A cube is built by calculating such a matrix for all Rkl's. Errors are detected by data in the cube that fall above or below a given threshold or are zero. For example, if there is a geometry error, most of the data points in a given matrix will be bad. If there is a statics error, on the other hand, the tr value will be bad, while other values are good. Further, if there
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is a receiver line error, a constant error will appear for all the points on that given receiver line (e.g. amplitude = 0). Thus, according to another aspect of the invention, in a QC process, useful event attributes (as used herein, "event attributes" comprise: for example, td, tr, Ad, Ar, Vd, and Vr) are compared to threshold values and QC problems are flagged based on that comparison (Figure 4C). The type of QC error is determined from the pattern of nonconformance with the particular event attribute. In some embodiments, the error is plotted in the velocity stack cube (e.g. with a specific color designating a specific type of error) and the errors are plotted along with the xy contours. Next, all flagged Sij an Rkl trace gathers are plotted.
According to a further embodiment a method for discriminating between statics, geometry, source and received problems is provided. This method is represented by Figure 4. A set of velocity stack trace envelopes is assembled, wherein the velocity stack trace envelopes have a particular shot and receiver location associated with each trace and include representations of multiple event arrivals. (Figure 4A) Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival. The velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event. At least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute (Figure 4B); discriminating between error type dependant upon the comparing (Figure 4C).
According to an alternative embodiment, rather than comparing the event attributes to threshold values, the event attributes for at least one trace are compared to the event attributes of at least one other trace. Errors are assigned to variances outside a predetermined level.
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Geometry and statics corrections: (Figure 5) (Figure 3)
According to an even further aspect of the invention, after assembling a set of velocity stack envelopes (Figure 5A) and picking a seismic event from that set of velocity stack trace envelopes (Figure 5B), the time delay between the first element location and the second element location is compared to a time delay threshold (Figure 5C). A geometry correction is then assigned dependent upon the comparison (Figure 5D).
According to an even further aspect of the invention a set of velocity stack envelopes are assembled (Figure 3A); some event arrivals representing the direct arrival and some representing events other than the direct arrival. At least one event attribute of at least one of the multiple event arrivals is compared to at least one event attribute of at least one other of the multiple event arrivals (Figure 3B). A statics correction is then assigned to a source receiver (Figure 3C).
According to an even further aspect of the invention, geometry corrections are provided by running triangulation or least squares location algorithms using the direct arrival attributes td tr(Sij(xy), Rmk(xy), Ad, Vd). A recomputed receiver location Sij(x',y') is then applied.
According to an even further aspect of the invention, static corrections are provided by running conventional residual statics algorithms using the refractor arrival attributes td tr(Sij(x'y'), Rmk(xy), Ar, Vr).
According to still an even further aspect of the invention a method for assembling, represented schematically in Figure 7, is provided. Compute the complex trace envelope of traces of a gather (Figure 7A), and sort the gather by a first clement line, a first element, a second element line, and a second element (Figure 7B). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Transform the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 7C), and pick events from the velocity stack trace envelopes (Figure 7D).
According to an even further aspect of the invention a method for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors is provided. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. First, band pass filter the traces (Figure 1 A), compute the complex trace envelope of
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traces of the gather (Figure 1C), sort the gather by a first element line, a first element, a second element line, a second element, and an offset bin (Figure 1E). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further, transform the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 1G). The traces are divergence corrected and positive bulk time shifted before transforming (Figure 1F). Pick events from the velocity stack trace envelopes (Figure 1H), determine statics error based on the picking (Figure 11), correct the statics error (Figure 1J), determine geometry error based on the picking (Figure 1K), and correct the geometry error (Figure 1L).
According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented by Figure 1. Each block in Figure 1 represents a hardware/software module as would be known to one of ordinary skill in the art. For a common element gather of traces, at least one element of the data comprises a shot and at least one other element of the data comprises a receiver. A means for computing the complex trace envelope of traces of the gather is provided (Figure 1C). Also provided is a means for sorting the gather by a first element line, a first element, a second element line, and a second element; defining a sorted gather of traces (Figure 1E). The means for computing and the means for sorting define a sorted gather of complex trace envelopes (Figure 1E). There is also provided a
means for transforming the sorted gather of complex trace envelopes into a set of velocity

stack trace envelopes (Figure 1G) and for picking events from the velocity stack trace
envelopes (Figure 1H).
According to an even further aspect of the invention a means for transforming the sorted gather of traces into a set of velocity stack trace envelopes provides slant stack transforming of the gather of traces and maxima detecting (Figure 1G). Also embodied in the present invention is a means for transforming the sorted gather of traces into a set of velocity stack trace envelopes providing muting the direct arrival and the data in the traces after the direct arrival and applying a tau-p transform (Figure 1G).
According to an even further aspect of the invention a means for picking is provided comprising cluster maxima detection (Figure 1H).
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According to an even further aspect of the invention a means for sorting is provided for sorting the gather by offset bin (Figure 1E).
According to still an even further aspect of the invention a means for divergence correcting the traces before the transforming is provided (Figure 1F).
According to an even further aspect of the invention a means for band pass filtering the traces is provided (Figure 1 A). Another nonlimitive aspect of the invention includes source array dependent band pass filtering (Figure 1 A).
According to an even further aspect of the inventions means for filtering out a DC component of the traces is provided (Figure 1D).
According to still an even further aspect of the invention a means for positive bulk time shifting the traces before the transforming is provided (Figure 1F).
According to an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data is provided before computing the complex trace envelope of traces of the gather (Figure 1B).
According to an even further aspect of the invention a system for correcting statics errors in a set of seismic data is provided. Schematically this is represented by Figure 3. Each block in Figure 3 schematically represents a hardware/software module as would be known by one skilled in the art. A means for assembling a set of velocity stack trace envelopes is provided (Figure 3A). Also provided is a means for comparing at least one event attribute of at least one of the multiple event arrivals to at least one event attribute of at least one other of the multiple event arrivals (Figure 3B). Further, a means for assigning a statics correction to a source-receiver is provided (Figure 3C). The statics correction is dependent upon the comparing. The velocity stack trace envelopes have a particular shot and receiver location associated with each trace and the velocity stack trace envelopes include representations of multiple event arrivals. The velocity stack trace envelopes also include event attributes comprising: time, amplitude, and velocity information for each event. Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival.
According to still an even further aspect of the invention a means for assembling. This is schematically represented by each block in Figure 7. Each block in Figure 7 represents a hardware/software module as would be known to one of ordinary skill in the art. A means for
Page 15

computing the complex trace envelope of traces of a gather (Figure 7A) is provided, and for sorting the gather by a first element line, a first element, a second element line, and a second element (Figure 7B). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. A means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 7C), and picking events from the velocity stack trace envelopes is provided (Figure 7D).
According to an even further aspect of the invention a system for discriminating between statics, geometry, source, and received problems is provided. This is schematically represented by Figure 4. Each block in Figure 4 represents a hardware/software module as would be known to one of ordinary skill in the art. Also provided is a means for assembling a set of velocity stack trace envelopes (Figure 4A). Further provided is a means for comparing at least one event attribute of at least one of the multiple event arrivals to a threshold value for at least one event attribute (Figure 4B). Still further provided is a means for discriminating between error type, dependent upon the comparing, and a means for assembling a set of velocity stack trace envelopes (Figure 4C). The velocity stack trace envelopes have a particular shot and receiver location associated with each trace and the velocity stack trace envelopes include representations of multiple event arrivals. The velocity stack trace envelopes include event attributes comprising: time, amplitude, and velocity information for each event. Some of the event arrivals represent the direct arrival and some represent events other than the direct arrival.
According to an even further aspect of the invention a system for correcting geometry errors in a set of seismic data traces is provided. This is represented schematically by Figure 5. Each block in Figure 5 represents a hardware/software module as would be known to one of ordinary skill in the art. The traces are related to a first element location and a second element location, one of the element locations being a shot location and the other of the element locations being a receiver location. Further, a means for assembling a set of velocity stack trace envelopes including offset bin information is provided (Figure 5A). Also provided is a means for picking a seismic event from the set of velocity stack trace envelopes (Figure 5B), a means for comparing a time delay between the first element location and the second element location to a time delay threshold (Figure 5C), and a means for assigning a
Page 16

geometry correction to at least one of the element locations; dependent upon the comparing (Figure 5D).
According to an even further aspect of the invention a means for assembling is provided comprising assigning the traces to offset bins and applying moveout correction to the traces (Figure 5A).
According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented in Figure 2. Each block in Figure 2 represents a hardware/software module as would be known to one of ordinary skill in the art. For a common gather of traces at least one element of the data comprises a shot and at least one other element of the data comprises a receiver. Also provided is a means for band pass filtering the traces, computing the complex trace envelope of traces of the gather (Figure 2A), filtering out a DC component of the traces and sorting the gather by a first element line, a first element, a second element line, a second element, and an offset bin. A sorted gather of traces is defined and computing and sorting define a sorted gather of complex trace envelopes (Figure 2B). Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 2C). The traces are divergence corrected and positive bulk time shifted before transforming. Also provided is a means for picking events from the velocity stack trace envelopes (Figure 2D).
According to still an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data before said computing the complex trace envelope of traces of the gather is provided (Figure 1B).
According to an even further aspect of the invention a system for automatically correcting geometry errors in seismic data including substantially linear seismic events in multiple element data is provided. This is represented schematically by Figure 8. Each block in Figure 8 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the trace (Figure 8A), computing the complex trace envelope of traces of the gather (Figure 8B), filtering out a DC component of the traces (Figure 8C), sorting the gather by a first element line, a first element, a second element line, a
Page 17
second element, and an offset bin (Figure 8D). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 8F). The traces are divergence corrected and positive bulk time shifted before transforming (Figure 8E). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 8G), determining geometry error based on the picking (Figure 8H) and correcting the geometry error (Figure 81).
According to an even further aspect of the invention a system for automatically correcting statics errors in seismic data including substantially linear seismic events in. multiple element data is provided. This is schematically represented by Figure 9. Each block in Figure 9 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the traces (Figure 9A), computing the complex trace envelope of traces of the gather (Figure 9B), filtering out a DC component of the traces (Figure 9C), sorting the gather by a first element line, a first element, a second element line, a second element (Figure 9D). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 9F). The traces are divergence corrected and positive bulk time shifted before the transforming (Figure 9E). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 9G), determining statics error based on the picking (Figure 1H) and correcting the statics error (Figure 91).
18

According to an even further aspect of the invention, a device for automatically detecting substantially linear seismic events in multiple element data is provided. This is schematically represented by a block diagram in Figure 10. At least one element of the data comprises a shot (Figure 10A) and at least one other element of the data comprises a receiver (Figure 10B), yielding a common element gather of traces (Figure 10C). The device comprises a means for computing the complex trace envelope of traces of the gather (Figure 10D) and a means for sorting the gather by a first element line, a first element, a second element line, and a second element (Figure 10E), wherein a sorted gather of traces is defined. The means for computing (Figure 10D) and the means for sorting (Figure 10E) define a sorted gather of complex trace envelopes (Figure 10F). The device also comprises a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 10G) and a means for picking events from the velocity stack trace envelopes (Figure 10H). The different means defined here are computer hardware comprising input devises, output devises, CPU, and memories, all adapted to carry out the program for the device.
According to an even further aspect of the invention a system for automatically detecting substantially linear seismic events in multiple element data, and for correcting geometry and statics errors is provided. This is schematically represented by Figure 1. Each block in Figure 1 represents a hardware/software module as would be known to one of ordinary skill in the art. At least one element of the data comprises a shot and at least one other element of the data comprises a receiver, for a common element gather of traces. Also provided is a means for band pass filtering the traces (Figure 1 A), computing the complex trace envelope of traces of the gather (Figure 1C), sorting the gather by a first element line, a
18A

first element, a second element line, a second element, and an offset bin (Figure 1E). A sorted gather of traces is defined. The computing and sorting define a sorted gather of complex trace envelopes. Further provided is a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes (Figure 1G). The said traces are divergence corrected and positive bulk time shifted before transforming (Figure 1F). Also provided is a means for picking events from the velocity stack trace envelopes (Figure 1H), determining statics error based on the picking (Figure 11), correcting the statics error (Figure 1 J), determining geometry error based on the picking (Figure 1K), and correcting the geometry error (Figure 1L).
According to still an even further aspect of the invention a means for applying a dispersion filter to the direct arrival data before said computing the complex trace envelope of traces of the gather is provided (Figure 1B).
Further embodiments and aspects of the invention will occur to those of skill in the art without departing from the spirit of the present invention.

WE CLAIM:
1. A device for automatically detecting substantially linear seismic events
in multiple element data, wherein at least one element of the data comprises
a shot and at least one other element of the data comprises a receiver, for a
common element gather of traces, the device comprising:
a means for computing the complex trace envelope of traces of the gather;
a means for sorting the gather by a first element line, a first element, a second element line, and a second element, wherein a sorted gather of traces is defined;
wherein said means for computing and said means for sorting are adapted to define a sorted gather of complex trace envelopes;
a means for transforming the sorted gather of complex trace envelopes into a set of velocity stack trace envelopes; and
a means for picking events from the velocity stack trace envelopes,
wherein the different means as defined herein are computer hardware means comprising input devices, output devices, CPU, and memories, all adapted to carry out the program for the device.
2. A device as claimed in claim 1, wherein said means for transforming
the sorted gather of traces into a set of velocity stack trace envelopes
comprises:
a means for slant stack transforming of the gather of traces; and a means for maxima detecting.
3. A device as claimed in claim 1, wherein said means for transforming
the sorted gather of traces into a set of velocity stack trace envelopes
comprises a means for muting the direct arrival and the data in the traces
after the direct arrival and applying a tau-p transform.
20

4. A device as claimed in claim 1, wherein said means for picking comprises cluster maxima detection.
5. A device as claimed in claim 1, wherein said means for transforming the sorted gather of traces into a set of velocity stack trace envelopes comprises a means for applying a tau-p transform.
6. A device as claimed in claim 1, wherein said means for sorting comprises a means for sorting the gather by offset bin.
7. A device as claimed in claim 1, wherein said means for transforming comprises a means for divergence correcting the traces beforehand.
8. A device as claimed in claim 1, wherein said means for computing comprises a means for band pass filtering the traces beforehand.
9. A device as claimed in claim 8, wherein said means for band pass filtering comprises a means for source array dependent band pass filtering.
10. A device as claimed in claim 1, wherein said means for computing comprises a means for filtering out a DC component of the traces afterwards.
11. A device as claimed in claim 1, wherein said means for transforming comprises a means for positive bulk time shifting the traces beforehand.
12. A device as claimed in claim 1, wherein said means for computing the complex trace envelope of traces of the gather comprises a means for applying a dispersion filter to the direct arrival data beforehand.
21

13. A device for automatically detecting substantially linear seismic events, substantially as herein described, particularly with reference to and as illustrated in the accompanying drawings.
There is disclosed a system for automatically detecting substantially linear seismic events in multiple element data, comprising, means for computing the complex trace envelope of traces of gather, means for sorting the gather by a first element line, a first element, a second element line, and a second element, means for transforming the sorted gather of complex trace envelopes defined by said means for computing and said means for sorting into a set of velocity stack trace envelopes, and means for picking events from the velocity stack trace envelopes.

Documents:

01194-cal-1998-abstract.pdf

01194-cal-1998-assignment.pdf

01194-cal-1998-claims.pdf

01194-cal-1998-correspondence.pdf

01194-cal-1998-description(complete).pdf

01194-cal-1998-drawings.pdf

01194-cal-1998-form-1.pdf

01194-cal-1998-form-2.pdf

01194-cal-1998-form-3.pdf

01194-cal-1998-form-5.pdf

01194-cal-1998-g.p.a.pdf

01194-cal-1998-letters patent.pdf

01194-cal-1998-priority document.pdf

1194-CAL-1998-FORM 27.pdf

1194-CAL-1998-FORM-27.pdf

1194-cal-1998-granted-abstract.pdf

1194-cal-1998-granted-claims.pdf

1194-cal-1998-granted-description (complete).pdf

1194-cal-1998-granted-form 2.pdf

1194-cal-1998-granted-specification.pdf

1194-cal-1998-priority document.pdf

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Patent Number

200215

Indian Patent Application Number

1194/CAL/1998

PG Journal Number

06/2007

Publication Date

09-Feb-2007

Grant Date

09-Feb-2007

Date of Filing

09-Jul-1998

Name of Patentee

PGS TENSOR, INC.

Applicant Address

10550,RICHMOND,SUITE 300, HOUSTON,TEXAS 77057,

Inventors:

#	Inventor's Name	Inventor's Address
1	FEDERICO DEVID MARTIN	5034,MOSS RUN DR- MISSOURI CITY, TEXAS 77459

PCT International Classification Number

G01V 1/36,G01V 1/28

PCT International Application Number

N/A

PCT International Filing date

PCT Conventions:

#	PCT Application Number	Date of Convention	Priority Country
1	08/891,263	1997-07-10	U.S.A.