MXPA97010022A - Method and apparatus for processing and exploring sismi signals - Google Patents

Abstract

A method and apparatus for the exploration of hydrocarbons comprising the steps of: obtaining a set of traces of distributed sistmic signals over a predetermined three-dimensional volume of the earth, dividing the three-dimensional volume into a plurality of analysis cells having porations of minus two seismic traces located in them, calculate the external products of the seismic traces located in them, calculate the external products of the seismic traces of the house cell M form the covariance matrix of each cell of those external products, calculate the own value dominant and the sum of the eigenvalues of the cavariance matrix of each cell and calculate a seismic attribute of the dominant eigenvalue for the sum of the eigenvalues of the covariance matrix of each cell, and form the map of the atribodies seismic groups of selected cells

Description

METHOD AND APPARATUS FOR PROCESSING AND EXPLORING SEISMIC SIGNS TECHNICAL FIELD The present invention relates to the general purpose of seismic exploration, and, in particular, to the apparatus and methods for the exploration and production of oil and gas by identifying structural characteristics and stratigraphics in three dimensions. BACKGROUND OF THE INVENTION In seismic exploration, seismic data are acquired along lines consisting of geophonic arrays near the coast or hydrophonic currents moving away from the coast. The geophones and hydrophones act as sensors to receive the energy that is transmitted to the earth and reflected back to the subsoil of the surface rocky interfaces. The energy is usually provided near the coast by Vibroseis® vehicles, which transmit impulses by shaking the earth at predetermined intervals and frequencies on the subsoil. Far from the coast, sources of air guns are usually used. Very sharp changes in the energy returned to the subsoil often reflect variations in the stratigraphic, structural and de fl ective contents of the reservoirs. In the realization of three-dimensional (3-D) seismic exploration, the principle is similar, however, the lines and arrays are more closely spaced to provide more detailed surface coverage. With REF: 26142 this high density coverage, it is necessary to register, store and process extremely large volumes of digital data before the final interpretation can be made. Processing requires extensive computational resources and complex programming and programming systems to amplify the signal received from the subsurface and silence the accompanying noise that masks the signal. Once the data is processed, the geophysicist staff collects and interprets the 3-D seismic information in the form of a 3D data cube (see Figure 1), which effectively represents a display of subsuperf- ficial features. Using this data cube, the information can be displayed in several ways. Horizontal time slice maps can be made at selected depths (see Figure 2). Using a computer workstation, a computer can also slice through the field to investigate the distribution of reservoirs in different seismic horizons. Slices or vertical sections can also be made in any direction using seismic data or wells. These maps can be converted to depth to provide a structural interpretation at a specific level. Seismic data have traditionally been acquired and processed for the purpose of forming images of seismic reflections. However, stratigraphic changes are often difficult to detect over traditional seismic display devices due to the limited amount of information that stratigraphic features present in a cross-sectional view. Although such views provide the opportunity to see a much larger portion of these characteristics, it is difficult to identify faulty surfaces within a 3-D volume, where no fault reflections have been recorded. The coherence and semblance (a measure of the coherence of multiple channels) are two measurements of the similarity or dissimilarity of the traces or lines of seismic record. When the coherence of two lines or seismic record lines increases, it is very likely that they are similar. The designation of a coherence measurement on a scale of zero to one, "0" indicates a greater lack of similarity, while a value of "1" indicates a total or complete similarity (ie, two identical strokes). The consistency of more than two strokes can be defined in a similar way. A method to calculate the coherence was described in a US Patent Application of Bahorich and Farmer (granted to Amoco Corporation), which has a serial number 08 / 353,934 and filing date of December 12, 1994. A method to calculate the profile was described in a US Patent Application Marfurt et al. . (granted to Amoco Corporation) having an application number 60 / 005,032 and a filing date of October 6, 1995. The invention of Marfurt et al included a search for brute force over candidate depressions and azimuths. Although both methods have proven to be good, they have some limitations. Improved resolution and computational speed are always desirable.

BRIEF DESCRIPTION OF THE INVENTION In accordance with the present invention, a multiple-trace eigenvalue decomposition process is described which is more robust and has higher resolution than previously known methods. In one embodiment of the invention, a method for the exploration of gas and oil is described. The method comprises the steps of accessing data sets of traces of seismic signals distributed over a predetermined three-dimensional volume of the earth; in an operating window that determines the external product of at least two data vectors formed from at least two seismic traces, forming a covariance matrix by summing the external products, calculating a seismic attribute that is a function of at least the dominant eigenvalue of the covariance matrix; and forming a map of the seismic attributes calculated on at least a part of the predetermined three-dimensional volume of the earth. In another embodiment of the invention, the process of the invention is encoded on a computer readable medium (e.g., magnetic disk, magnetic tape, CD-ROM (Compact Disc Read Only Memory), etc.) to detect the operation of a computer to calculate the seismic attributes. In other embodiments of the invention, a map is prepared from the process described above and the map is used to locate oil and gas deposits. This technique is particularly suitable for interpreting fault planes within a 3-D seismic volume and for detecting very fine 3-D stratigraphic characteristics. This is because the seismic traces are cut by a fault line that generally has a seismic character to that of the seismic traces on either side of the fault. The measurement of the similarity of the seismic trace, (ie, coherent continuity or 3-D) together with a time slice reveals lines of low coherence along those fault lines. Such coherence values may reveal critical subsurface details that are not readily apparent on traditional seismic sections. Also calculated the coherence along a series of slices of time, those fault lines identify flats or surfaces with faults.

The numerous and other advantages and features of the present invention will become readily apparent from the following detailed description of the invention, the embodiments described herein, the claims, and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a perspective representation of the information obtained from 3-D seismic data processing; Figure 2 is a perspective representation of a horizontal time slice of the 3-D seismic data processed according to the prior art; Figure 3 is a drawing describing two adjacent seismic traces; Figures 4 to 8 are schematic diagrams describing the coherence of a pair of seismic traces according to the present invention; Figure 9 is a perspective representation of a functioning window analysis cube; Figures 10A, 10B, and 10C are schematic diagrams of groups of seismic traces; Figures HA, 11B and 11C are schematic diagrams of two dimensional analysis windows; Figure 12 is an elementary process flow diagram; and Figures 13A, 13B and 13C are perspective representations of the same horizontal time slice according to the inventions of Bahorich et al., Marfurt et al, and the present invention.

DETAILED DESCRIPTION PE THE INVENTION Although this invention is capable of being realized in many different forms, the drawings are shown, and will be described here in detail / several specific embodiments of the invention. It should be understood, however, that the present description should be considered an example of the principles of the invention and that it is not intended to limit the invention to the specific modalities or algorithms described herein. Before describing the process of the invention, the underlying operation principle will be described. Consider two traces or lines of registers ti and t2 over a window of time or window of specific depth of N samples for which consistency was evaluated. The representative diagram of the record lines or lines and the relevant analysis window is shown in FIGURE 3. The first trace or line of record ti consists of the time series (tu, t? 2 / ..., tw) and the second trace or record line t2 consists of time series (t2 ?, t22, ..., t2N) • In those two series, the first index refers to the number of trace or record lines (ie, trace or line of record 1 or trace or line of record 2), while the second index refers to the sample number. By plotting a trace or record line against the other in the familiar two-dimensional Cartesian coordinate system, a better understanding of the meaning of coherence can be obtained in the context of the present invention. Graph equivalent time samples of the two trace lines or register lines, ie, the pairs of points (tu, t2?), (T? 2, t22), -, (tiN, t2N)], produce a cross-plot of the two time series. By making the x-axis represent the first trace or line of record ti and the y-axis and the second trace or line of record t2, the diagram described in FIGURE 4 is obtained as a result. This is the pattern formed by those points that show coherence of two lines or lines of registration. The general form of these two correlated trace lines or lines is a set of points represented by an ellipse. This ellipse is a generalization since it does not represent each individual point but it describes the "total" nature of all the points. The major and minor axes of this ellipse will be oriented in a direction that is determined by the geometry of the paired points. The lengths of the two axes are also determined by this geometry. A typical representation of those points and the corresponding ellipse is shown in FIGURE 5. The directions and magnitudes of the major and minor axes of the ellipse can be represented by two scaled vectors with the largest vector oriented along the major axis and the shortest vector along the minor axis. The magnitudes of these two vectors correspond to two eigenvalues of the data covariance matrix and the normalized vectors correspond to the eigenvectors. The eigenvectors, scaled by their respective eigenvalues, denote the magnitudes and directions of the major and minor axes. The "main component" corresponds to the eigenvector that is associated with the dominant eigenvalue. The following figures (FIGURE 6 through 8) are intended to give an intuitive understanding of the mechanics behind the previous discussion. In those FIGURES, the traces or log lines were constructed using amplitude variations and simple phases, and the effect of those variations was observed on the eigenvalues and associated eigenvectors.

FIGURE 6 demonstrates how to generate two traces or record lines identical to a 45 degree line, (ie, an ellipse with the minor axis collapsed to zero). The "zero length" indicates that the second eigenvalue is "zero" and indicates that the eigenvector corresponding to the dominant eigenvalue is aligned with the major axis. The consistency is maximum, with a value of one. The situation for two traces or registration lines that have equal amplitudes and a phase difference of 45 degrees is dead in FIGURE 7. This shows how a phase deviation lengthens the minor axis and therefore increases the magnitude of the second eigenvalue . The two eigenvectors scaled by their respective eigenvalues are also shown. Due to the difference in those traces or registration lines, the coherence was reduced to a value of less than one. Finally, FIGURE 8 allowed both phase and amplitude to vary. The two traces or registration lines both have a phase deviation of 45 degrees and an amplitude ratio of 2 to 1. The resulting ellipse has a minor axis different from zero (the second eigenvalue is not zero), which reflects the difference of phase. In addition, the ellipse and the eigenvectors rotated due to the difference in amplitude. Again, amplitude and phase variations produce a reduction in coherence.

The main point of the previous discussion is to show heuristically that coherence can be expressed as a function of the eigenvalues,? I and? 2, and the eigenvectors Vi and v2. Functionally, an expression for coherence is: Coherence = / (? I,? 2, vx, v2) (1) This procedure for two strokes can easily be extended to any number of desired strokes. From a practical point of view, the computational load increases with the increase in the number of strokes and the limitations imposed only by the available computing power. For a set of 3-D seismic data, this analysis can be repeated on a window of analysis of movement or operation in space and time (or space and depth), resulting in a measure of coherence in the center of the window of movement. The result is a 3-D data set consisting of coherence values defined on the original data volume. From the following discussion it will be evident that an advantage of this process is that the different aspects of the data are distributed between the eigenvalues and the eigenvectors. Information, such as amplitude and phase, can now be analyzed and treated in a robust and rigorous way. The resolution, for example, can be improved by manipulating the eigenvalues and the eigenvectors. The benefits can be observed visually in the calculated coherence slices. Another important aspect of the coherence values according to the present invention is that they exhibit discontinuity sensitivity to the original data and reveal very fine geological features, such as faults and channels. Returning to the process of the present invention, the first step is to obtain or have access to a set of three-dimensional seismic data. Such data are in the form of traces of seismic signals distributed over a three-dimensional volume of the earth. The methods by which such data is obtained and reduced to a digital format for processing as 3-D seismic data are well known to those skilled in the art. Such data are routinely acquired by geophysical sellers who specialize in land studies or studies of the ocean. Such data are also sold or licensed by sellers and are usually contained or stored on magnetic tapes to be transferred to the memory of a seismic workstation. The next step is to divide the 3-D data set into a plurality of analysis cells or cubes 20 (See Figure 9). These cubes 20 perform the function of dividing or classifying the seismic data into groups or cells for further processing. In effect, an analysis cube sweeps through the entire seismic data set or 3-D data cube 30. Each analysis cube 20 comprises a stack of time layers, generally rectangular, flat, 22. With the purpose of simplifying, the 3-D 30 data cube, the analysis cube 20, and the time layers 22 are shown in the form of parallelepipeds or cubes of right angles (generically a "cell"). Those skilled in the art will appreciate the simplicity of the rectangular geometry to perform repetitive operations on the 3-D data set. Other geometry and cell shapes are possible and can be guaranteed under the circumstances. Returning to Figure 10, each time layer 22 or slice has portions of seismic traces ti (only one is shown to avoid clutter in the drawings) passing through it. In Figure 9, nine strokes are described, placed in a uniformly spaced 3 by 3 grid. Five strokes can be used in a star-shaped pattern (See Figure 10A) or three strokes (See Figure 10B). An asymmetric arrangement is preferred. Nine strokes in each time layer are often better than three strokes. At least two strokes can be used. To help visualize the concept of the invention, the reader is referred to Figures HA and 11B. In particular, it is often difficult to visualize these concepts in nine dimensions (as in the case of 9 strokes). In Figures HA and 11B, a two-dimensional operation window 24 (or analysis window) is shown with just two traces ti and t2 contained therein. Each trace (See Figure 11C) comprises a time series of N samples t2 = (t2 ?, t22, ..., t2n) The analysis window 24 of Figure 11C is further divided into a plurality of rectangular, vertically stacked, time layers 22. Before proceeding, it should be understood that, in the choice of window size and separation, there is a relationship between the resolution and stability. In other words, small analysis windows or cubes allow a higher spatial or temporal frequency in the estimation of the resulting parameter, but give less statistical stability or less degrees of freedom to those estimated. On the other hand, very large windows, have low resolution and tend to spoil the data so that important geological features can be lost.

Returning to Figure 11C, the data points within each time layer 22 define seismic data vectors (here a matrix of 1 by 2, where N = 2). As such, the two-dimensional time layers 11C (or the three-dimensional time layer of Figure 9) form or define windows of vectors. In this way, nine strokes (N = 9) will result in a data vector that has nine elements. The external product of the data vector within each vector window or time layer 22 results in a matrix of N per N. In this way a data vector of nine elements gives rise to a matrix of 9 by 9. Adding those matrices (a matrix for each vector window) results in a covariance matrix of N by N for the entire analysis window 24 (or the analysis cube 20). Thus, if the analysis cube comprises nine time layers, new matrices of N by N are added to form a co-variance matrix of N by N. According to the present invention, a very useful and non-obvious measure of the The coherence of the trace is obtained by calculating the eigenvalues of the covariance matrix. In particular, the largest or dominant eigenvalue of the covariance matrix and the sum of the eigenvalues of the covariance matrix are calculated. The relationship of these two numbers represents the size of the dominant eigenvalue in relation to the sum of eigenvalues. It also indicates the variability of the strokes within the analysis cube. Expressed mathematically, a useful seismic attribute is represented by: where? i are the eigenvalues of the covariance matrix, and? i is the dominant eigenvalue. As such, ? it is an indication that so many point elements of the seismic data vectors are correlated (See Figures 4 and 5). Each and every one of the eigenvalues of the respective covariance matrix need not be expressly calculated. Those skilled in the art know that there are methods to calculate only the dominant eigenvalue (for example, the power method, Rayleigh quotient, [the quicker of the two], etc.). In addition, it is also known that the sum of the diagonal elements of the covariance matrix is equal to the sum of the eigenvalues of that covariance matrix. For convenience, the relationship (ie, a measure of coherence) of equation (2) can be assigned to the center of the analysis cube 20 or to the analysis window 22. It should be noted that one advantage of using the dominant eigenvalue is that it tends to show more directly the variability of the strokes within the analysis window. The dominant eigenvector may not be a measure of variability (ie, coherence). To effect this coherence measurement, the analysis cube 20 or the analysis window 22 effectively sweeps (ie, laterally and vertically) through the entire 3-D volume of FIGURE or all of the strokes of FIGURE HA. Preferably, adjacent analysis cubes 20 or vector windows 22 overlap each other (see windows 24, 24 'and 24"of FIGURE HA) Superposition improves spatial resolution. 20 which sweeps the entire 3D data volume 30 and the coherence measurement assignment of equation (2) is an array of coherence values assigned along each trace at the location of each data vector., the 3D data volume is converted into a 3D "coherence cube". The coherence data or measurements contained within the coherence cubes are more conveniently interpreted by presenting the coherence data in the form of a map of seismic attributes. Such a map is often in the form of a display of those values of coherence that are found along the subsoil that passes through the coherence cube. Two examples are a plane that passes through a common horizontal time slice, and a curved subsoil that passes through a seismic horizon line selected by a seismic interpreter. Another example is a representative line of geological deposition time to capture characteristics of the same geological age. The coherence values are easily displayed or displayed for interpretation when presented as a gray scale (for example, white indicating the highest coherence and black indicating the lowest coherence) or another color scale (See Patent US 4,970,699 for a "Method for Tracing Color Maps of Geophysical Data"). Interpretive work stations can be used Landmar and GeoQuest, for example, to see and interpret faults and stratigraphic characteristics by loading the coherence cube as a seismic volume. Such work stations are commonly used by those skilled in the art. Unprocessed 3D seismic data can be conveniently loaded into the workstation by means of a magnetic tape or disk that is encoded with instructions for the computer to perform the process described above. Programming and programming systems for visualization (eg, Landmark Six Cube programming and programs) can be used to quickly slice through the coherence cube to help understand complex fault relationships. The presented coherence, including impressions in the form of seismic attribute maps, can reduce the interpretation cycle time when used in the selection of seismic lines or interpretation, allowing the interpreter to work around poor data areas. In addition, fine stratigraphic features and complex faults, which are not readily apparent in traditional seismic display devices, can be quickly identified and interpreted. FIGURES 13A, 13B and 13C provide comparisons of the same seismic information presented and processed by other processes and according to the present invention. The differences are easily evident. Of course, the process of the invention is carried out more conveniently by writing a computer program to perform the steps already described. Such processes are carried out routinely in previously identified work stations. An elementary process flow diagram is illustrated in FIGURE 12. In one embodiment of the invention, a computer program is written in FORTRAN 77 to carry out the process already described. Seismic data 3-D 30 are read in the memory. Based on the size and content of the available seismic data, a start step 32 is performed, initial values are assigned to the program parameters, stabilized at the data intervals, preliminary checks are made, and the size of the data is set. window. The parameters set by default are read or the user selects the options read. The processing 34 then begins. In particular, the subroutines 36 are evoked to sweep the volume of data with an analysis cube. Within each analysis cube, a subroutine 38 calculates the covariance matrix, and another subroutine 40 calculates the dominant eigenvalues, the sum of the eigenvalues and the resulting coherence value. Finally, the results 42 are combined and the calculated values are stored 44 in the form of a coherence cube. Subsequently, a workstation operator can access the coherence cube to present the selected portions (eg, slice of time through the cube) in a CRT 46, to create an impression or map of seismic attributes 48, for perform an additional analysis or to transfer them to a memory or a tape 50 for further processing elsewhere. Those skilled in the art should be careful in using the method of the invention with respect to what is known about the stratigraphy and geology of the region covered by the 3-D study. Consistency maps for several 3-D studies have been tested. At reasonable data quality depths, approximately 90% of faults can be easily identified. The faults were identified on coherence maps that were very thin on seismic sections, but clearly present on the coherence maps due to the robustness of the method and the perspective of the fault pattern map. Since coherence maps can be tested or run over uninterpreted time slices, the present invention offers means to greatly accelerate the mapping of the structural framework and to reveal detail relationship of failures that could otherwise be interpreted only to through the tedious search for faults.

Specific examples Consistency maps were generated along the horizons taken and salt / slate diapirs were clearly identified far from the coasts.

In other places, mud and gas volcanoes were clearly indicated using the process of the invention. Several slices of coherence time showed remarkable details of stratigraphic features, such as abandoned river channels, mud flows, point bars and underwater canyons. In seismic sections, these characteristics were sometimes evident, but, in some cases, they were not identifiable even with close scrutiny. This invention, like that of Bahorich et al.

And Marfurt et al., Provides a method for revealing flawed drawings within a 3-D volume where no fault reflections have been recorded. Faults are often critical to the accumulation of oil. A fault can form a seal by cutting a structural or stratigraphic feature so that oil is trapped against the fault. On the other hand, if the faulty plane contains debris that has not been cemented, it can form a fluid conduit. This can allow the hydrocarbons to push up the plane with faults to the feature and become trapped or escape the feature by pushing up the plane with faults outside it. In this way, fault lines can predict flow patterns in a reservoir and communication between injection and production wells, for example. Seismic discontinuities can also provide the necessary link to allow the prediction of reservoirs between the wells and establish the continuity of the reservoir and the flow patterns through a field. The coherence technology can be used to find, identify and map the structural and sedimentological characteristics of the subsoil, such as faults, salt diapirs, nonconformities, channel systems, karstified zones, and carbonate reef facies which are commonly associated with trapping and storage of hydrocarbons. Therefore, this technology helps to find, extract and produce hydrocarbons. In addition, it is used to identify shallow and deep drilling risks (for example, places where there is gas that is very close to the surface or where there are instabilities). Yet another example is the use of the invention to search for leak paths of known reservoirs or storage caverns below the ground. The mapping of coherence maps of 3-D seismic features is an extremely powerful and efficient tool to draw both structural and stratigraphic maps. The new method is particularly sensitive to any lateral variation in the character of the wave train and is therefore particularly sensitive to the common causes of lateral variations in the wave train (i.e., fault shifts or stratigraphic variations). Thus, the object of the invention encompasses a process, the devices in which the process is recorded in the form of computer instructions, the product (eg, a map) of that process, and the manner in which such a product it is used in the exploration of gas and oil. From the above description, it should be noted that numerous variations, alternatives and modifications will be apparent to those skilled in the art. Accordingly, this description should be considered only as illustrative and for the purpose of teaching those skilled in the art the manner of carrying out the invention. For example, the seismic traces could have been described as having an equal separation. The traces separated in a non-uniform manner (See FIGURE 10C) can be conveniently converted into uniform separations by interpretation. As another example, it may be useful to filter the traces that form the data vector to eliminate dependencies. A median filter can be used to classify the elements of each data vector. Edge cuts can be used to achieve greater uniformity.

In addition, other algorithms can be used to measure the similarity of nearby regions of seismic data or to generate the "coherence cube". The coherence value or seismic attribute of equation (2) serves as a more than robust estimate or measure of the signal discontinuity within geological formations as well as signal discontinuities through erosional failures and nonconformities. Other combinations of eigenvalues of the covariance matrix are suggested (for example, arithmetic mean, square root of the mean, mean, mean, square root of the sum of squares, square root of the product of the squares, minimum, maximum, sum , product, etc.). In addition, the process of the invention can be combined with other attributes (e.g., AVO slope, etc.) and also be applied to multi-component seismic data. Also certain features of the invention can be used independently of other features of the invention. For example, the geological features identified in accordance with the present invention can be superimposed on a speed map to provide means to verify velocity crossings. Furthermore, although coherence slice maps by themselves are very powerful mapping tools, when used in conjunction with amplitude recognition maps and depression maps, there is a promise of technological progress for effective mapping of the maps. Gulf of Mexico or similar sources with easily available 3-D seismic data. It is believed that detailed mapping of structural and stratigraphic maps will be accelerated by drawing a map view on a map and less by obtaining line by line. Interpretation in a "recognition" data map view offers a significant improvement in the quality and quantity of the interpretation. In addition, the process of the invention is inherently fast. Such speed helps to quickly make bids when concessions are available. Finally, it should also be understood that the principle of the invention could be equally applicable to other fields (for example, passive sonar, in which case the sensors could be acoustic and the signal sources could be hostile submarines, earthquakes and detection systems). detonation of nuclear weapons, in which case the sensors could be seismic and the signal sources could be epicenters of earthquakes or explosions, astronomical interferometry, where the sensors could be radio telescopes and the sources of signals could be distant galaxies or quasars, and phasing arrays, in which case the sensors could be antenna arrays) where the signals (eg, radar, sonar, radio frequency energy, etc.) are processed to image or locate changes in the structure represented by such images. Thus, it should be appreciated that various modifications, alternatives, variations and changes may be made without departing from the spirit and scope of the invention as defined in the appended claims. Of course, it is intended to cover all those modifications involved within the scope of the claims by means of the appended claims.

It is noted that in relation to this date, the best method known to the applicant to carry out the aforementioned invention, is that which is clear from the present description of the invention. Having described the invention as above, property is claimed as contained in the following:

Claims (60)

1. A method for the exploration of hydrocarbons, characterized in that it comprises the steps of: a) obtaining a set of distributed seismic tracings on a predetermined three-dimensional volume of the earth; b) dividing the three-dimensional volume into a plurality of vertically stacked and generally separated horizontal time layers and arranging such time layers into a plurality of cells extending laterally and vertically, each of the time layers having portions of at least two seismic traces located in them that define a data vector; c) calculating in each of the time layers of such cells the external products of the data vector; d) combine the external products to obtain a covariance matrix for each of the cells; e) calculate in each of the cells a measure of the coherence of the seismic traces, where the measure of coherence is at least one function of the largest eigenvalue of the covariance matrix; and f) forming a map of seismic attributes from a plurality of measures of coherence of the seismic traces.

2. The method according to claim 1, characterized in that in step (f) a map is formed by presenting the measures of coherence in relation to a surface passing through a predetermined seismic horizon.

3. The method according to claim 1, characterized in that in step (f) the map is formed presenting the measures of coherence in relation to a surface passing through a predetermined time line.

4. The method according to claim 1, characterized in that in step (b) the cells comprise analysis cubes having at least five seismic traces located therein; and wherein to carry out step (c) each external product is in the form of a 5 by 5 matrix.

5. The method according to claim 4, characterized in that in step (b) the cells comprise analysis cubes having portions of at least nine seismic traces located therein; and where the data vectors have nine elements.

6. The method according to claim 5, characterized in that in step (b) nine seismic traces are arranged in a 3 by 3 grid.

7. The method in accordance with the claim 1, characterized in that in step (b) the cells are less than 100 milliseconds thick.

8. The method according to claim 1, characterized in that step (e) is carried out in the time domain.

9. The method according to claim 1, characterized in that step (e) is carried out: calculating the largest eigenvalue of the covariance matrix, calculating the sum of the eigenvalues of the covariance matrix, and calculating the eigenvalue relation larger for the sum of the eigenvalues of the covariance matrix.

10. The method in accordance with the claim 9, characterized in that the sum of the eigenvalues of the covariance matrix is calculated by forming the sum of the diagonal elements of the covariance matrix.

11. The method according to claim 1, characterized in that in performing step (b) one of the two seismic traces in each cell is located in an adjacent cell so that the cells are spatially superimposed on one another.

12. A method for locating features, faults and underground contours, characterized in that it comprises the steps of: a) acquiring 3-D seismic data covering a predetermined volume of the earth, the data comprising seismic traces characterized by time, position and amplitude; b) dividing at least a portion of the volume into at least one array of relatively small, adjacent, superimposed three-dimensional analysis cubes, wherein each of the analysis cubes contains at least three laterally separated seismic traces and dividing each analysis cube into a plurality of sample intervals, so that each sample interval defines a plurality of one-by-three data vectors; c) calculate a seismic attribute for each cube that is a function of the dominant eigenvalue of a covariance matrix formed from the external products of the data vectors; and d) storing the seismic attributes of the analysis cubes to present them in the form of a two-dimensional map of subterranean features.

13. The method in accordance with the claim 12, characterized in that in step (c) the seismic attribute is a function of the ratio of the dominant eigenvalue to the sum of at least two of the eigenvalues of the covariance matrix of the cube.

14. The method in accordance with the claim 13, characterized in that in step (c) the seismic attribute is a function of the relation of the dominant eigenvalue to the sum of all the diagonal elements of the covariance matrix.

15. The method in accordance with the claim 14, characterized in that the seismic attribute is assigned to the center of its analysis cube.

16. The method in accordance with the claim 15, characterized in that in step (b) it is carried out on a plurality of slices of time in addition to including the step of: e) presenting the seismic attributes of successive time slices passing through the centers of the 'analysis' cubes , to identify the invariable characteristics of space and time.

17. In seismic exploration, where 3-D seismic data comprises reflected seismic energy recorded as a function of time to produce a series of seismic traces, and where a computer that is adapted to process such seismic traces is used, a manufactured article characterized in that it comprises: a means that is readable by a computer and that contains instructions for the computer to perform a process comprising the steps of: (a) having access to 3-D seismic data over a predetermined volume, the data comprises vectors of seismic signals characterized by time, position and amplitude; and (b) finding the similarity of the nearby regions of the 3-D seismic data of such volume by: (1) dividing at least a portion of the data into an array of relatively small, adjacent, superimposed three-dimensional analysis cubes in where each of the analysis cubes contains at least two data vectors; and (2) calculate a seismic attribute for each cube that is a function of the principal eigenvalue of a covariance matrix that is formed from a sum of external products of such cube vectors.

18. The article of manufacture according to claim 17, characterized in that the means contains instructions for the computer to perform the step (2) of calculating the relation of the main value to the sum of the eigenvalues of the covariance matrix.

19. The article of manufacture according to claim 17, characterized in that the means contains instructions for the computer to perform step (2) to calculate the ratio of the main eigenvalue to the sum of the diagonal elements of the covariance matrix.

20. The article of manufacture according to claim 19, characterized in that the means contains instructions for the computer to perform the step (1) of forming analysis cubes having a generally rectangular array of at least five seismic traces located therein; and wherein the covariance matrix is at least a five by five matrix and is formed from at least three external product matrices.

21. The article of manufacture according to claim 20, characterized in that the medium contains instructions for the computer to assign the seismic attributes to the center of its analysis cube.

22. In seismic exploration, where the reflected seismic energy is recorded as a function of time to produce a series of seismic traces, a method characterized in that it comprises the steps of: (a) determining the external product of two data vectors formed from at least two seismic traces; (b) forming a covariance matrix by adding the external products of step (a); (c) calculating a seismic attribute that is a function of at least the principal eigenvalue of the covariance matrix of step (b); (d) repeating the steps of (a) through (c) through at least a portion of at least one time window; and (e) forming a map of the seismic attributes on the time window.

23. The method according to claim 22, characterized in that step (c) is carried out by calculating the ratio of the main eigenvalue to at least a partial sum of the eigenvalues of the covariance matrix.

24. The method according to claim 22, characterized in that step (c) is carried out by calculating the ratio of the main eigenvalue to at least a partial sum of the diagonal elements of the covariance matrix.

25. The method according to claim 22, characterized in that step (d) is carried out using at least one seismic trace from the previous operation of step (a) and at least two seismic traces that are located adjacent to at least one seismic trace .

26. The method according to claim 22, characterized in that step (a) comprises the steps of: (1) having access to the 3-D seismic data on a predetermined volume of the earth, the seismic steps of the seismic data 3- D are characterized by time, position and amplitude; and (2) dividing a portion of the volume into at least one time window comprising an array of relatively small, superimposed three-dimensional analysis cubes containing at least two seismic traces.

27. A method of seismic exploration, characterized in that it comprises the steps of: a) reading a 3-D seismic data set comprising traces of seismic signals distributed over a volume of the earth; b) selecting at least one horizon slice of the volume and forming on them cells which are arranged in rows and columns extending laterally, each of the cells comprises at least three seismic lines that generally extend therethrough; c) calculate for each of the cells; (1) the external product of the data vectors defined by a plurality of time slots on each side of the center of the cell; (2) a covariance matrix through the external products of step (1); and (3) at least the largest eigenvalue of the covariance matrix; and d) examining the eigenvalues of the cells along at least one horizon slice.

28. The method in accordance with the claim 27, characterized in that step (3) is carried out by displaying a representation of the largest eigenvalues of the cells through at least one horizontal time slice.

29. The method according to claim 28, characterized in that the representation is a function of the largest eigenvalue of the cell and the sum of the eigenvalues of the covariance matrix of said cell.

30. In the seismic exploration, where the reflected seismic energy is registered as a function of time to produce a series of seismic traces, a method characterized because it comprises the steps of: (a) arranging 3-D seismic data in three-dimensional analysis cubes * relatively small, superimposed, containing a plurality of seismic traces; (b) determine the external product of the data vectors defined by the analysis cubes; (c) forming a covariance matrix for each cube by summing the external products of step (b); (d) calculating a seismic attribute that is a function of the relation of the main eigenvalue of each covariance matrix to the sum of all the eigenvalues of the covariance matrix; and (e) arrange the seismic attributes to be presented as a map.

31. A device, characterized in that it comprises: computer readable media containing instructions for a process comprising the steps of: (1) reading in the memory the 3-D seismic data covering a predetermined volume of the earth; (2) classify digitatal 3-D seismic data in an array of relatively small three-dimensional cells, where each cell contains at least three seismic traces; (3) calculating in each of the cells a coherence value from the eigenvalues of a covariance matrix formed from a plurality of external products of at least three traces; and (4) store the coherence values of the cells to present them in the form of a two-dimensional map of the subterranean characteristics represented by the coherence values.

32. The device according to claim 31, characterized in that in step (3) the coherence value is at least a function of the largest of the eigenvalues of the covariance matrix.

33. The device according to claim 32, characterized in that the covariance value is a function of the largest eigenvalue and a sum of the eigenvalues.

34. The device according to claim 31, characterized in that the computer readable media are selected from the group consisting of a magnetic tape, a magnetic disk, an optical disk and a CD-ROM.

35. A method for locating features, faults, and underground contours, characterized in that it comprises the steps of: a) obtaining the seismic data covering a predetermined volume of the earth; b) dividing the volume into an array of relatively small three-dimensional cells, wherein each of the cells is characterized by at least two vectors of seismic data located therein; c) calculate a covariance matrix from the extreme values of the data vectors; d) plot the map of a representation of the eigenvalues of the covariance matrix.

36. The method according to claim 35, characterized in that step (c) is carried out using a covariance matrix formed by adding a plurality of external products.

37. The method according to claim 35, characterized in that step (d) is carried out by mapping the ratio of the largest eigenvalue to the sum of the eigenvalues.

38. A method for exploring hydrocarbon deposits, characterized in that it comprises the steps of: a) obtaining a map of seismic attributes of seismic coherence values 3-D for a predetermined three-dimensional volume of the earth, such a map is generated using a computer and a program for the computer that instructs the computer to perform the following steps: (1) read the data and store the volume in an array of three-dimensional, relatively small cells, where each cell has at least two vectors of seismic data located in them; and (2) calculate in each of the cells a coherence value for the seismic traces that is a function of the eigenvalues of the covariance matrix formed from the external products of the data vectors; and (b) use the map to identify soil structural and sedimentological characteristics commonly associated with trapping and storage of hydrocarbons.

39. The method in accordance with the claim 38, characterized in that it also includes the step of using the map to identify drilling risks.

40. The method in accordance with the claim 39, characterized in that it also includes the step of drilling in a place identified in step (b).

41. The method according to claim 38, characterized in that the program instructs the computer to perform step (a) (2) to: (i) calculate the largest eigenvalue of each covariance matrix and the sum of the eigenvalues of the covariance matrix; and (ii) calculate the ratio of the largest eigenvalue to the sum.

42. The method according to claim 41, characterized in that it includes in step (i) the program instructs the computer to calculate the sum of the eigenvalues by calculating the sum of the diagonal elements of the covariance matrix.

43. A seismic map prepared by a process, characterized in that it comprises the steps of: (1) having access, by means of a computer, to a set of data comprising traces of seismic signals distributed over a predetermined three-dimensional volume of the earth. (2) dividing the three-dimensional volume into a plurality of cells that are arranged in a time and space, each of the cells having located in them a plurality of data vectors; (3) calculating in each cell a plurality of external products formed from the data vectors located therein; (4) combine the external products to form a matrix for each cell; (5) calculate the dominant eigenvalue of the matrix and the sum of the diagonal elements of the matrix; and (6) presenting the largest eigenvalue in relation to the sum for each matrix of a predetermined group of cells passing through a predetermined surface.

44. The seismic map according to claim 43, characterized in that step (6) is performed by obtaining the ratio of the dominant value to the sum of each matrix of the predetermined group of cells passing through the predetermined surface.

45. The seismic map according to claim 43, characterized in that in step (2) each of the data vectors has at least three elements.

46. The seismic map according to claim 43, characterized in that step (4) is carried out by adding all the external products.

47. A map for oil and gas exploration, characterized in that it comprises: a) a generally flat medium for recording visually perceptible images on it; and b) a plurality of images on such a medium that are a function of the dominant eigenvalue of a covariance matrix that is formed from the external products of an operating window of the data vectors representing a 3-D seismic survey.

48. The map according to claim 47, characterized in that the images are a function of the ratio of the dominant eigenvalue to the sum of the eigenvalues of the covariance matrix.

49. The map according to claim 47, characterized in that the medium is the face of a cathode ray tube.

50. The map according to claim 47, characterized in that the images are a function of the ratio of the documented eigenvalue to the sum of the diagonal elements of the covariance matrix.

51. The map according to claim 47, characterized in that the operation window comprises an analysis cube comprising at least three time layers; wherein each time layer contains a data vector in it; and wherein the data vector comprises at least three elements of seismic traces.

52. The map according to claim 51, characterized in that the eigenvalues are assigned to the center of each analysis cube.

53. An exploration map formed by a process, characterized in that it comprises the steps of: a) forming a coherence cube from 3-D seismic data data vectors, the coherence cube comprises a three-dimensional array of coherence values that are at least a function of the dominant eigenvalues of the covariance matrices of the data vectors; and b) presenting the coherence values as an image on a surface according to a predetermined transfer criterion.

54. The map according to claim 53, characterized in that the coherence values are assigned to three-dimensional coordinates that generally coincide with the elements of the data vectors.

55. The map according to claim 53, characterized in that in step (b) the surface is a planar plane and the predetermined transfer criterion is that the planar plane coincides in general with a time slice through the time data 3-D.

56. The map according to claim 53, characterized in that in step (a) each coherence value is at least a function of the dominant eigenvalue and the sum of the eigenvalues of the respective covariance matrix.

57. A device to be used by a computer workstation of the type used in oil and gas exploration, characterized in that it comprises a computer-readable medium and that it contains a representation of a coherence cube, the coherence cube comprises data elements of the coherence of 3D seismic data, each of the measurements is a function of the eigenvalues of a covariance matrix formed from the sum of at least two external products of at least two seismic data vectors.

58. The device according to claim 57, characterized in that the data vectors are characterized by space and time coordinates and where the coherence measurements are assigned to the space and time coordinates.

59. The device according to claim 58, characterized in that each of the measurements is at least a function of the dominant eigenvalue of the respective covariance matrix.

60. The device according to claim 59, characterized in that each of the measurements is at least a function of a sum of eigenvalues.