Five-dimensional seismic data optimization method for crack prediction

Abstract

The invention provides a fissure prediction-oriented five-dimensional seismic data optimization method, and the method comprises the steps: taking the azimuth and offset information in a gather as the basis, and employing an optimization strategy of an ellipse fitting degree and fissure strength comprehensive evaluation index; and taking the optimal combination of the division number of the azimuth angles and the offset range as a data optimization method for crack prediction. The optimized data comprehensively considers the crack prediction strength and the data fitting degree, and provides reliable quality guarantee for crack prediction.

Description

Technical Field

[0001] The invention relates to the field of geophysical exploration research, and in particular to a five-dimensional seismic data optimization method for fracture prediction. Background Art

[0002] In the exploration of various types of reservoirs in oil fields, such as tight sandstone, oil shale, igneous rock and buried hill, fractures are the main migration and storage space of oil and gas, and fracture prediction is an important link in complex oil and gas exploration. The distribution of fractures in reservoirs is very complex. The traditional post-stack seismic coherence, curvature and other attributes have low fracture prediction accuracy. Different attributes have different sensitivities to different lithology and physical properties, which makes it difficult to select appropriate attributes. The fracture prediction method of five-dimensional seismic pre-stack gathers uses the azimuth anisotropy variation characteristics contained in the longitudinal wave signal in the data to solve the problem of fracture azimuth and density. Since the azimuth and offset information are added to the five-dimensional seismic data gathers, different fracture prediction results can be obtained by adjusting the number of azimuth divisions and the offset range. The selection of the number of azimuth divisions and the offset will affect the results of fracture prediction.

[0003] In traditional five-dimensional gather crack prediction methods, the number of azimuths and offset ranges are often manually selected. The crack prediction effect is greatly affected by human factors. The experimental workload of combining the number of azimuths and offset ranges is large and the efficiency is low. There is a lack of automatic optimization methods for the azimuth and offset ranges of five-dimensional gathers. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a five-dimensional seismic data optimization method for fracture prediction that overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a five-dimensional seismic data optimization method for fracture prediction is provided, the data optimization method comprising:

[0006] Step 1: Read the five-dimensional seismic data, analyze the seismic trace header information, and obtain the azimuth and offset information of each trace in the five-dimensional trace gather;

[0007] Step 2: Select the five-dimensional target gather and read the seismic amplitude data of all the tracks at the corresponding time in the gather according to the target layer;

[0008] Step 3: Given an offset range and a number of azimuth divisions, select data according to the azimuth and offset, perform ellipse fitting, and calculate the ellipse fitting degree and fracture strength;

[0009] Step 4: Change the number of azimuth divisions and repeat step 3;

[0010] Step 5: Change the offset range and repeat step 4;

[0011] Step 6: Calculate the comprehensive evaluation index based on the ellipse fitting degree and crack strength, and select the best azimuth offset distance division scheme for crack prediction.

[0012] Optionally, the five-dimensional seismic data is a pre-stack data gather including azimuth and offset information in the header;

[0013] The azimuth and offset information is obtained in the file header.

[0014] Optionally, in step 2, reading the seismic amplitude data of all channels at corresponding times in the channel gather according to the target layer specifically includes: for each channel in the channel gather, taking the amplitude value within the time window tw with the target layer time t0 as the center, and calculating the average value as the seismic amplitude value.

[0015] Optionally, in step 2, reading the seismic amplitude data of all channels at corresponding times in the gather according to the target layer specifically includes: for each channel in the gather, taking the target layer time t0 as the starting point, finding the local amplitude maximum value as the seismic amplitude value.

[0016] Optionally, in step 3, an offset range is given with a given starting offset and an ending offset, and the seismic amplitude data of all channels of the target layer corresponding to the time within the offset range is obtained according to the method in step 2. Given an azimuth division number, the starting azimuth and the ending azimuth of each sub-angle range are calculated according to the division number, and the root mean square amplitude of the seismic amplitude data in each sub-angle is calculated respectively to obtain the central angle and the root mean square amplitude data of the sub-angle as the input data for ellipse fitting.

[0017] Optionally, the fitting degree of the ellipse obtained by the ellipse fitting in step 3 specifically includes:

[0018] Calculate the polar diameter corresponding to each central angle according to the ellipse fitting equation;

[0019] Calculating the variance of the polar diameter and the root mean square amplitude;

[0020] The crack strength is calculated using the values ​​of the major and minor axes obtained by ellipse fitting.

[0021] Optionally, changing the number of divisions of the azimuth angle in step 4 specifically includes:

[0022] The number of divisions of the azimuth angle starts from n0 and is divided into steps of d. n Increase in sequence until no data can be obtained at a certain sub-angle;

[0023] If the number of tracks in a sub-angle is less than 5, add the track data of the sub-angle in the opposite direction.

[0024] Optionally, changing the offset range in step 5 specifically includes:

[0025] Given an offset moving step, given a starting offset;

[0026] The end offset is calculated in sequence according to the step length until the end offset is greater than the maximum offset;

[0027] Change the starting offset distance by the step size and repeat the operation until the starting offset distance is larger than the maximum offset distance.

[0028] Optionally, the calculating of the comprehensive evaluation index in step 6 specifically includes: taking the ratio of crack strength to ellipse fitting as the comprehensive evaluation index.

[0029] Optionally, the optimal azimuth offset distance division scheme for crack prediction in step 6 specifically includes:

[0030] Traverse all combinations of offset distance and angle division number;

[0031] Find out the number of angle divisions and the offset range where the maximum value of the global comprehensive evaluation index is located.

[0032] The present invention provides a five-dimensional seismic data optimization method for crack prediction, the data optimization method comprising: step 1: reading five-dimensional seismic data, parsing seismic trace header information, and obtaining azimuth and offset information of each trace in the five-dimensional gather; step 2: selecting a five-dimensional target gather, and reading seismic amplitude data of all traces at the corresponding time in the gather according to the target layer; step 3: given an offset range, given an azimuth division number, selecting data according to the azimuth and offset, performing ellipse fitting, and calculating the ellipse fitting degree and crack strength; step 4: changing the azimuth division number, repeating step 3; step 5: changing the offset range, repeating step 4; step 6: calculating a comprehensive evaluation index according to the ellipse fitting degree and crack strength, and optimizing the best azimuth offset division scheme for crack prediction. The optimized data comprehensively considers the crack prediction strength and the data fitting degree, and provides reliable quality assurance for crack prediction.

[0033] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0035] Figure 1 A flowchart of the optimization of five-dimensional seismic data for fracture prediction provided by an embodiment of the present invention;

[0036] Figure 2 Schematic representation of different azimuth intersection divisions and offset range evaluation indicators provided in the embodiments of the present invention;

[0037] Figure 3 A three-dimensional display diagram of the preferred comprehensive evaluation index of the gather data provided by the embodiment of the present invention;

[0038] Figure 4 A schematic diagram of an offset distance preferably ranging from 200 to 800 provided in an embodiment of the present invention;

[0039] Figure 5 A comparison chart of crack prediction results between preferred data and non-preferred data provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0041] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0042] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0043] Example 1

[0044] Step 1: Read the five-dimensional seismic data, analyze the seismic trace header information, and obtain the azimuth and offset information of each trace in the five-dimensional trace gather;

[0045] Read five-dimensional seismic data, analyze seismic trace headers, and obtain the azimuth and offset information of each trace;

[0046] The 5D seismic data is a pre-stack data set that contains offset and azimuth information in the header. The offset and azimuth information is obtained in the file header.

[0047] The trace header data package in the five-dimensional seismic data contains a total of 240 bytes of offset and azimuth information. The offset and length of the offset and azimuth information in the trace header data can be customized by the user, and the offset and azimuth values ​​are obtained by parsing the offset and length. For example, if the offset position is 37 and the length is 4 bytes, the file pointer is used to locate the corresponding position, read 4 bytes, and then convert them into an offset value of 240. The azimuth information can be obtained similarly.

[0048] Step 2: Select the five-dimensional target gather and read the seismic amplitude data of all the tracks at the corresponding time in the gather according to the target layer;

[0049] Determine the data file corresponding to the target gather, the number of gather tracks, and the offset position and length of each gather track in the corresponding seismic data file through the given line number, and obtain the sampling start time t of the seismic data start and sampling interval t interval .

[0050] For a given target layer, calculate the offset position corresponding to the target layer at time t0 All traces in the track gather are traversed in sequence to obtain the seismic amplitude values ​​of all traces corresponding to time t0.

[0051] The amplitude value is calculated by the following two methods:

[0052] (1) For each trace in the gather, set the time window t w , taking the target layer time t0 as the center, taking the time window The amplitude values ​​of all n points in [d1, d2, ..., d n ], calculate the average value of n points, that is, the earthquake amplitude value

[0053] (2) For each trace in the gather, starting from the target layer time t0, search upward for the local maximum position t closest to t0. up , search downward for the local maximum position t closest to t0 down , if t0-t up <t down -t0, then select t up The value of the position is taken as the final earthquake amplitude value, otherwise t down The value of the position is taken as the earthquake amplitude value.

[0054] The acquired seismic amplitude is recorded in the format of offset, azimuth and amplitude value.

[0055] Step 3: Given an offset range and a number of azimuth divisions, select data according to the azimuth and offset, perform ellipse fitting, and calculate the ellipse fitting degree and fracture strength;

[0056] A given offset range is to set a certain starting offset and ending offset, such as a starting offset of 200 and an ending offset of 500.

[0057] Obtain all seismic amplitude data of the target layer at the corresponding time within the offset range, that is, obtain the amplitude data that meets the set offset requirement in all the recorded data in step 2, such as all amplitude data of 200≤offset≤500.

[0058] Given a certain number of azimuth divisions, the starting azimuth and ending azimuth of each sub-angle range are calculated according to the number of divisions, that is, the sub-angle size d is calculated by the number of sub-angles n θ =2π / n, and then calculate the starting angle and ending angle of each sub-angle range [0,d θ ],[d θ ,2d θ ],...[(n-2)d θ ,(n-1)d θ ].

[0059] The root mean square amplitude of the seismic amplitude data in each sub-angle is calculated respectively to obtain the central angle and root mean square amplitude data of the sub-angle, that is, for any sub-angle range such as [0,d θ ], and further select the offset distance from the above screening results to meet the requirements of 0≤azimuth≤d θ The m amplitude values ​​[d1, d2, ..., d m ], calculate the root mean square of m amplitude values, that is Calculate the central azimuth Get the central azimuth angle and the root mean square amplitude d rms Value pair.

[0060] If the number of tracks in the angle division is less than 5, the track data of the angle division in the opposite direction will be added. That is, m≤5, and the tracks that meet 0≤azimuth≤d θ Or 180≤azimuth≤d θ +180 for all amplitude values.

[0061] Perform ellipse fitting calculation. For the n central azimuths and root mean square amplitude d rms Value pairs, according to Convert to rectangular coordinates, use the least squares method to fit the ellipse, and obtain the minor axis a, major axis b, and major axis direction α of the ellipse.

[0062] Calculate the fitting degree. For n pairs of central azimuth angles and root mean square amplitude values, calculate the ellipse radius of each central azimuth angle in the fitting ellipse. For example, for the central azimuth angle θ, according to the formula Calculate the corresponding ellipse radius For a given n RMS amplitude values ​​d1, d2, ...d n , whose mean is The total sum of squares Regression sum of squares The goodness of fit can be calculated using the total sum of squares SST and the regression sum of squares SSR

[0063] Calculate the crack strength. Use the values ​​of the major axis and minor axis obtained by ellipse fitting to calculate the crack strength. The formula is as follows:

[0064] Step 4: Change the number of azimuth divisions and repeat step 3;

[0065] Change the number of azimuth divisions, i.e. the number starts from n0 and the step size is d n The number of divisions of the azimuth angle starts from 3 and increases in steps of 1 to obtain the number of divisions of 3, 4, 5, ..., n, .... For the number of divisions of n angles, n angle ranges [0, d θ ],[d θ ,2d θ ],...[(n-2)d θ ,(n-1)d θ ] If data cannot be obtained for a certain sub-angle, stop repeating step 3, otherwise repeat step 3.

[0066] Step 5: Change the offset range and repeat step 4;

[0067] According to step 1, obtain the minimum and maximum offsets, such as 200 to 1500. Given an offset moving step, such as 300, given a starting offset, such as 200, and then obtain the ending offset in sequence according to the step length until the ending offset is greater than the maximum offset. You can get ending offsets of 500, 800, 1100, 1400, and finally get the offset ranges of 300 to 500, 300 to 800, 300 to 1100, and 300 to 1400;

[0068] Change the starting offset according to the step size, and repeat the above operation until the starting offset is greater than the maximum offset. If the starting offset is changed according to the step size, such as 300+200=500, the starting offset is 500. After the starting offset is changed, the above steps of modifying the ending offset are repeated, and finally the offset ranges are obtained in turn: 500-800, 500-1100, and 500-1400; continue to change the starting offset and repeat the above calculations.

[0069] Repeat step 4 for each offset range.

[0070] Step 6: Calculate the comprehensive evaluation index based on the ellipse fitting degree and crack strength, and select the best azimuth offset distance division scheme for crack prediction.

[0071] For the ellipses with different azimuth angles and different offset ranges calculated in steps 4, 5, and 3, the fitting degree and fracture intensity values ​​are obtained. The comprehensive evaluation index G is calculated by using the fitting degree and fracture intensity values ​​through the following formula:

[0072] The number of azimuth divisions and the offset range corresponding to the maximum value of the comprehensive evaluation index G are selected, as well as the preferred azimuth position and offset range for fracture prediction of five-dimensional seismic data under the set initial value and step size.

[0073] The initial step size is given a larger value, and the calculation range is gradually refined using this method, and a smaller step size is given to calculate it once.

[0074] Example 2

[0075] like Figure 1 As shown, Figure 1 The flow chart of the method for optimizing the gather data for fracture prediction of the present invention is as follows. The method for optimizing the gather data for five-dimensional seismic data includes the following steps:

[0076] Step 101: read the five-dimensional seismic data, parse the seismic header information, and obtain the azimuth and offset information of each channel in the five-dimensional channel gather. The offset and azimuth information are obtained by the offset and length given by the user in the channel header data. For example, if the offset position is 37 and the length is 4 bytes, the file pointer can be used to locate the corresponding position, read 4 bytes, and then converted into an offset value of 240. The azimuth position is 41 and the length is 4 bytes. The file pointer can be used to locate the corresponding position, read 4 bytes, and then converted into an azimuth value of 120.

[0077] Step 102: Select a five-dimensional target gather, and read the seismic amplitude data of all the tracks at the corresponding time in the gather according to the target layer. For example, if the target layer time is 1200ms, according to method 1, the amplitude values ​​of all 10 points in the time window [-1.17E+06, -928955, -1.35E+06, -2.47E+06, -1.40E+06, 152645, -615897, -651592, -60616.4, 1.08E+06] are taken with the target layer time 1200ms as the center, and the average value of the 10 points -740581.54, which is the seismic amplitude value, is calculated; according to method 2, with the target layer time 1200ms as the starting point, the local maximum position 1196ms closest to 1200ms is searched upward, and the local maximum position 1202ms closest to 1200ms is searched downward. If 1202ms is closer to 1196, the value 152645 at 1202 is selected as the final seismic amplitude value.

[0078] Step 103: Given an offset range and an azimuth segmentation number, data is selected according to the azimuth and offset, and ellipse fitting is performed to calculate the ellipse fitting degree and fracture strength. Given an azimuth of 7 and an offset range of 2000 to 2300, the ellipse fitting degree is 0.976236 and the fracture strength is 0.711701 through ellipse fitting calculation.

[0079] Step 104: Change the number of azimuth angle divisions, repeat step 103, change the number of azimuth angle divisions, that is, the number starts from 3 and increases in sequence with a step size of 1 until data cannot be obtained at a certain sub-angle.

[0080] Step 105: Change the offset range, such as 200-1500. Given an offset moving step, such as 300, given a starting offset, such as 200, and then calculate the ending offset in sequence according to the step until the ending offset is greater than the maximum offset. You can get ending offsets of 500, 800, 1100, 1400, etc., and finally get the offset ranges of 300-500, 300-800, 300-1100, 300-1400 in sequence; change the starting offset in step, and repeat the above operation until the starting offset is greater than the maximum offset. As above, change the starting offset in step, such as 300+200=500, then the starting offset is 500. After the starting offset is changed, continue to repeat the above ending offset modification steps, and finally get the offset ranges of 500-800, 500-1100, 500-1400 in sequence; continue to change the starting offset and repeat the above calculation.

[0081] Step 106: After calculation, comprehensive evaluation indicators of different azimuth divisions and offset range combinations can be obtained. Figure 2The data in the table are all the evaluation data obtained by calculation. Figure 3 To display the results graphically, the number of azimuth angles is selected as 6 and the offset range is 200-800 according to the maximum value of the evaluation index 1.75. Figure 3 The optimal offset range is consistent with the distribution of five-dimensional gather data points. According to the ellipse fitting degree and the comprehensive evaluation index of fracture intensity calculation, the optimal azimuth offset division scheme for fracture prediction is selected.

[0082] The number of azimuth divisions and the offset range corresponding to the maximum value of the comprehensive evaluation index G are selected, as well as the preferred azimuth position and offset range for fracture prediction of five-dimensional seismic data under the set initial value and step size.

[0083] The initial step size is given a larger value, and then the calculation range is gradually refined using this method, and a smaller step size is also given to calculate it once.

[0084] Beneficial effects: Based on the azimuth and offset information in the gather, the present invention adopts the optimization strategy of ellipse fitting and comprehensive evaluation index of crack strength, and takes the optimal combination of the number of azimuth divisions and offset range as the data optimization method for crack prediction. The optimized data comprehensively considers the crack prediction strength and the fitting degree of the data, providing reliable quality assurance for crack prediction.

[0085] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A five-dimensional seismic data optimization method for fracture prediction, characterized in that: The data optimization method comprises: Step 1: Read the five-dimensional seismic data, analyze the seismic trace header information, and obtain the azimuth and offset information of each trace in the five-dimensional trace gather; Step 2: Select the five-dimensional target gather and read the seismic amplitude data of all the tracks at the corresponding time in the gather according to the target layer; Step 3: Given an offset range and a number of azimuth divisions, select data according to the azimuth and offset, perform ellipse fitting, and calculate the ellipse fitting degree and fracture strength; Step 4: Change the number of azimuth divisions and repeat step 3; Step 5: Change the offset range and repeat step 4; Step 6: Calculate the comprehensive evaluation index based on the ellipse fitting degree and crack strength, and select the best azimuth offset distance division scheme for crack prediction.

2. A five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The five-dimensional seismic data is a pre-stack data gather including azimuth and offset information in the header; The azimuth and offset information is obtained in the file header.

3. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The step 2 specifically includes reading the seismic amplitude data of all channels at the corresponding time in the gather according to the target layer: for each channel in the gather, taking the amplitude value within the time window tw with the target layer time t0 as the center, and calculating the average value as the seismic amplitude value.

4. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The step 2 of reading the seismic amplitude data of all the tracks at the corresponding time in the track gather according to the target layer specifically includes: for each track in the track gather, taking the target layer time t0 as the starting point, finding the local amplitude maximum value as the seismic amplitude value.

5. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: In the step 3, an offset range is given as a given starting offset and an ending offset, and all seismic amplitude data of the target layer corresponding to the time within the offset range are obtained according to the method in step 2. A number of azimuth divisions is given, and the starting azimuth and the ending azimuth of each sub-angle range are calculated according to the number of divisions. The root mean square amplitude of the seismic amplitude data in each sub-angle is calculated respectively, and the central angle and the root mean square amplitude data of the sub-angle are obtained as the input data of the ellipse fitting.

6. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The fitting degree of the ellipse obtained by the ellipse fitting in step 3 specifically includes: Calculate the polar diameter corresponding to each central angle according to the ellipse fitting equation; Calculating the variance of the polar diameter and the root mean square amplitude; The crack strength is calculated using the values ​​of the major and minor axes obtained by ellipse fitting.

7. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: Changing the number of divisions of the azimuth angle in step 4 specifically includes: The number of divisions of the azimuth angle starts from n0 and is divided into steps of d. n Increase in sequence until no data can be obtained at a certain sub-angle; If the number of tracks in a sub-angle is less than 5, add the track data of the sub-angle in the opposite direction.

8. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: Changing the offset range in step 5 specifically includes: Given an offset moving step, given a starting offset; The end offset is calculated in sequence according to the step length until the end offset is greater than the maximum offset; Change the starting offset distance by the step size and repeat the operation until the starting offset distance is larger than the maximum offset distance.

9. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The calculation of the comprehensive evaluation index in step 6 specifically includes: taking the ratio of crack strength to ellipse fitting degree as the comprehensive evaluation index.

10. The five-dimensional seismic data optimization method for fracture prediction according to claim 1, characterized in that: The optimal azimuth offset distance division scheme for crack prediction in step 6 specifically includes: Traverse all combinations of offset distance and angle division number; Find out the number of angle divisions and the offset range where the maximum value of the global comprehensive evaluation index is located.

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