CN112394393B - CRP gather data volume reconstruction method - Google Patents
CRP gather data volume reconstruction method Download PDFInfo
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- CN112394393B CN112394393B CN201910745649.9A CN201910745649A CN112394393B CN 112394393 B CN112394393 B CN 112394393B CN 201910745649 A CN201910745649 A CN 201910745649A CN 112394393 B CN112394393 B CN 112394393B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
Abstract
The invention discloses a CRP gather data volume reconstruction method, which comprises the following steps: designing a calculation grid, and obtaining critical incidence angle data of each CRP point on a grid point; carrying out interpolation and smoothing on the critical incident angle data of each CRP point to obtain critical incident angle plane data about a top interface or a bottom interface of a target layer; and removing the gather data of which the angle gather of each CRP point is larger than the corresponding critical incident angle by using the critical incident angle plane data of each CRP point to obtain a gather reconstruction data volume. Compared with the traditional AVO inversion method, the reservoir can be accurately detected by reconstructing the data volume by using the processed gather.
Description
Technical Field
The invention relates to the technical field of petroleum geophysical exploration, in particular to a seismic data processing and explaining technology, and particularly relates to a CRP gather data volume reconstruction method.
Background
In recent years, with the continuous improvement of exploration position of lithologic hydrocarbon reservoirs, prestack AVO attribute inversion and prestack elastic parameter inversion technologies are developed greatly and widely applied to lithologic prediction and oil-gas exploration, and the prediction precision of the prestack AVO attribute inversion and prestack elastic parameter inversion technologies is influenced by input data besides the inversion method. As input data for pre-stack AVO attribute and pre-stack elastic parameter inversion, the quality of a pre-stack CRP (common reflection point) gather has a large influence on the inversion result. It is widely recognized that the problems of signal-to-noise ratio, wavelet consistency, incidence angle range, residual dynamic correction, far-path distortion and the like of the CRP gather have great influence on the pre-stack or post-stack inversion result, so that the setting of the incidence angle range of the pre-stack gather is very necessary. The critical incident angle of the CRP angle gather input by the conventional prestack inversion technique is usually set to a certain fixed incident angle and AVO inversion of the target layer is performed, and when a gather larger than the critical incident angle is selected for AVO inversion, waveform distortion or polarity inversion may be generated by the gather with a large incident angle, which may cause trouble to the inversion result. In practice, even in the same research area, the critical incident angles of the target layers with AVO characteristics on each point are different due to geological conditions, geophysical acquisition, processing technology and other influences.
The AVO inversion technology is based on a Zoeppritz equation, when a Poisson ratio parameter is used for replacing a transverse wave speed parameter and an incidence angle is smaller than 30 degrees, the Zoeppritz equation is simplified into a Shuey approximate equation, and the most remarkable characteristic of the equation is that the reflection amplitude is only increased along with the increase of the incidence angle. Koefoed (1955) emphasizes that in a limited range of incidence angles (0 ° to 30 °), the shape of the reflection coefficient curve is only slightly affected by the exchange of incident and underlying media, and due to the presence of critical reflections and the difference in the rate of change of the reflection coefficient amplitude, a significant difference occurs at larger incidence angles, because large-angle seismic reflection amplitudes are more strongly attenuated by the absorption of the formation during seismic wave propagation, and the motion-corrected stretching effect is more severe during seismic data processing, and seismic reflection waveform deformation is easily generated after superposition. Some patents such as the patent of invention CRP gather true amplitude recovery method based on AVO characteristics (application number: 201310666981.9) disclose that on the basis of Zoeppritz elastic wave dynamics theory, the method aims at keeping the relation that the pre-stack amplitude changes along with the offset, and seismic data are subjected to elimination fitting through a Shuey approximate equation to obtain a more accurate true amplitude effective signal. Currently, an effective workflow is not established in the processing of the incidence angle range of the prestack CRP gather, and the following problems mainly exist in the existing prestack CRP gather data:
(1) The critical incident angle size at each CRP point is often not uniform in general;
(2) The pre-stack CRP gather data with larger incidence angle is used as pre-stack inversion data to be input or stacked, and the obtained result is often inconsistent with the actual situation.
Disclosure of Invention
The invention aims to overcome the problem that an inversion structure is inconsistent with the actual situation due to the adoption of a large incidence angle in the prior art, and provides a method for reconstructing a CRP gather data volume.
In order to achieve the above purpose, the invention provides the following technical scheme:
a method of CRP gather data volume reconstruction comprising the steps of:
designing a computational grid, and obtaining critical incidence angle data of each CRP point on the grid point;
step two, carrying out interpolation and smoothing treatment on the critical incident angle data of each CRP point to obtain critical incident angle plane data related to a top interface or a bottom interface of a target layer;
and step three, removing the gather data of which the angle gather of each CRP point is larger than the corresponding critical incident angle by using the critical incident angle plane data of each CRP point to obtain a gather reconstruction data volume.
Preferably, the third step further includes performing prestack inversion and poststack attribute extraction by using the gather reconstruction data volume.
Preferably, the first step includes:
a. carrying out corresponding calculation grid design on the research area;
b. converting the CRP gather data subjected to dynamic correction into an angle domain to obtain CRP angle gather data, and performing superposition processing on the CRP angle gather data with an incidence angle within an incidence angle threshold range to obtain a superposition data body;
c. performing well-seismic calibration on the stacked data volume by using well logging data and geological stratification data on the well, determining a top interface and a bottom interface of a target layer, selecting the top interface or the bottom interface as seed points, and performing automatic horizon tracking by using the stacked data volume to obtain horizon data;
d. projecting the horizon data on the calculated grid points onto a CRP angle gather, and performing horizon tracking on the angle gather to obtain gather horizon data of the CRP angle gather;
e. using the gather horizon data, associated critical angle of incidence data values are determined for the angle gathers of the respective CRP points.
Preferably, the threshold range of incidence angles is less than or equal to 30 degrees.
Preferably, the method for determining the critical incident angle comprises:
and establishing a fitting relation curve of a series of amplitude-incidence angle data points on the angle gather horizon data at the CRP point, wherein the incidence angle data corresponding to the extreme point on the fitting curve is the critical incidence angle.
Preferably, if the critical incident angle determined from the extreme point is greater than 30 degrees, the critical incident angle is set to 30 degrees.
According to another aspect of the present invention, there is provided an electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of any one of the above.
Compared with the prior art, the invention has the beneficial effects that:
the data volume reconstructed by the gather processed by the method is used as data input of pre-stack inversion, the obtained result is more accurate than the result obtained by using the data volume reconstructed by the gather which is not processed by the method and adopting the same parameter and technique, and the method has high inosculation with well data, and compared with the traditional AVO inversion method, the method can accurately detect the reservoir stratum by using the data volume reconstructed by the gather which is processed. Taking a certain block explored in south as an example, the finding of known well drilling in a research area shows that the result of the method is better matched with well drilling data, and a gas-containing reservoir area can be accurately predicted.
Description of the drawings:
FIG. 1 is a block diagram of the steps of the method of the present invention.
FIG. 2 is a schematic diagram of determining a critical incident angle in a CRP angle trace set according to an embodiment of the present invention.
FIG. 3 is a schematic view of a reconstructed CRP gather according to an embodiment of the invention.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to test examples and specific embodiments. It should be understood that the scope of the above-described subject matter is not limited to the following examples, and any techniques implemented based on the disclosure of the present invention are within the scope of the present invention.
The invention relates to a technology for performing subsequent prestack inversion by utilizing CRP angle gather data to perform target layer-based critical incident angle limitation and gather rejection processing, which can accurately and effectively predict a reservoir stratum of a target layer section and achieve relatively high coincidence rate with an aboveground AVO forward modeling type.
The specific implementation mode of the method is as follows:
1. and designing a calculation grid, and solving the critical incidence angle data of each CRP point on the grid point.
The study area is designed with a corresponding computational grid, which is typically n lines of Xm tracks. In practice, the computational grid should be set correspondingly according to the computational accuracy and the seismic data. The grid parameters comprise grid intervals, grid number and the like, the size of the grid parameters can be determined according to grid distribution and accuracy requirement conditions of AVO critical incidence angles to be extracted, and in principle, the larger the usually set grid interval is, the lower the calculation accuracy is, and some characteristic information can be lost; the smaller the grid spacing, the higher the accuracy of the calculation and the more detailed the plotted results. The size of the set grid is determined according to actual conditions, and the set grid is usually regular.
And converting the CRP gather data after dynamic correction into an angle domain to obtain angle gather data, and performing superposition processing on the CRP angle gather data within a set certain incidence angle range to obtain a superposition data volume. Usually, the tracks with incidence angle greater than 30 ° for the buried depth of the target layer are not involved in the overlay processing, and the relevant overlay data volume is obtained. In addition, the CRP gather data can be further processed to improve the signal-to-noise ratio, the resolution, the fidelity and the like. The angle gather conversion can select a calculation formula to perform angle gather conversion according to actual conditions, and the conversion formula of the angle gather can be as follows:
in the formula (1), theta is an incident angle of an angle track, x is an offset, v is a root mean square velocity, and t 0 Is a zero offset pairWhen the journey is made.
In the formula (2), alpha is the incident angle of the angle track, v int Is the layer velocity, v rms Is the root mean square velocity, t is the two-way travel time, x is the offset.
And performing well-seismic calibration on the stacked data volume by using the logging data and geological stratification data on the well, determining top and bottom interfaces of a target layer, selecting a certain interface as a seed point, and performing automatic horizon tracking by using the stacked data volume to obtain horizon data, wherein the interface is generally wave crest or wave trough reflection. The automatic tracking method generally adopts an automatic tracking method based on waveform characteristics. On the premise of giving a seed point, the method searches points similar to the waveform structural feature of the seed point in a given time window range. The waveform structural characteristics comprise wave crests and wave troughs, and the wave crests and the wave troughs are automatically identified track by track in the seismic data volume, and the time window range is generally 20ms.
And projecting the horizon data on the calculation grid points onto the CRP angle gather, and automatically tracking the horizon on the angle gather to obtain the gather horizon data of the CRP angle gather.
The gather horizon data is used to determine the associated critical angle of incidence data values for the angle gathers of the CRP points on the computational grid. Establishing a fitting relation curve of a series of amplitudes on the angle gather horizon data of the CRP points, namely angle of incidence data points, wherein the angle of incidence data corresponding to extreme points of the fitting curve is the critical angle of incidence; if the critical angle of incidence determined by the extreme point is greater than 30 °, the critical angle of incidence is set to 30 °. The extreme points can be generally divided into two types, namely maximum points and minimum points, and the determination of the critical incident angle by selecting which extreme point is selected depends on actual conditions such as a fitting curve, AVO characteristics and the like. Generally, the critical incident angle of most CRP angle gathers is between 14 and 30 degrees, specifically, a sampling interval is set between 0 and 30 degrees, and amplitude data corresponding to each sampling incident angle point on a fitting curve is extractedObtaining the amplitude data J corresponding to each incident angle by taking the data values i And forming an amplitude data set { J i }; the size of the sampling interval can be determined according to actual conditions, and is generally calculated by taking 0.05 degrees. The curve fitting method can generally adopt a least square method for fitting, and the calculation formula of extreme value solving is as follows:
J max ＝max{J i } (3)
J min ＝min{J i } (4)
the critical angle of incidence is calculated as follows:
J max →θ r (5)
J min →θ r (6)
j in formulae (3) to (6) i (i =1, 2.... N.) is the amplitude value corresponding to the i-th sampling incidence angle on the fitted relation curve of the amplitude-incidence angle data points, J max Is the maximum value of amplitude, θ r The data value of the critical incident angle is corresponding to the extreme value.
Step two, carrying out interpolation and smoothing treatment on the critical incident angle data of each CRP point to obtain critical incident angle plane data related to a top interface or a bottom interface of a target layer;
and carrying out gridding interpolation, smooth filtering and other processing on the critical incidence angle data of each CRP point on the grid points to obtain the critical incidence angle data of each CRP point. The processing of gridding interpolation, smooth filtering and the like is to interpolate critical incidence angle data of a computational grid (usually, the computational grid is greater than 1 line X1, and generally 10 lines X10) into 1 line X1 according to a gridding interpolation algorithm, and set certain filtering parameters for the critical incidence angle after gridding computation to perform smooth filtering, so that some critical incidence angle mutation points are eliminated, and the result is closer to the result of the actual critical incidence angle, thereby obtaining the critical incidence angle data of each CRP point. The gridding interpolation algorithm can be a least squares method, a weighted average method, a (universal) kriging method and the like, and the calculation method is determined according to actual conditions.
And step three, removing the gather data of which the angle gather of each CRP point is larger than the corresponding critical incident angle by using the critical incident angle plane data of each CRP point to obtain a gather reconstruction data volume. And performing calculation such as prestack inversion and poststack attribute extraction by using the reconstructed data volume.
Example 1
In the example, CRP gather data reconstruction is carried out on a section of a marine Longmaxi group of a certain three-dimensional work area before prestack inversion.
Considering the relatively flat condition of a section of target layer of the Longmaxi group, the calculation grid is designed into 20X 20 lines, the CRP gather after dynamic correction can be converted into an angle gather by using a ray tracing method, the range of the superposed incidence angle is set to be 0-30 degrees, and the data volume is subjected to well-seismic calibration by using well data after superposition. Determining the top interface and the bottom interface of the target layer, setting the top interface of the target layer as an interpretation interface, namely stronger peak reflection, taking comprehensive consideration that the interpretation grid is 20 lines X20 channels as the calculation grid, carrying out gridding interpolation calculation on the interpretation grid, interpolating to 1 line X1 channel to obtain horizon data, and projecting the horizon data onto a CRP angle gather to obtain gather horizon data. In the example, the critical incidence angle calculation is carried out on the calculated grid points by using the trace set horizon data and the CRP angle trace set, the least square method is used for carrying out data fitting, the incidence angle range of 0-30 degrees is determined to be used as an extreme value calculation range, the sampling interval of the incidence angle is set to be 0.05 degrees to obtain an amplitude data set, the extreme value is calculated for the data set, and the critical incidence angle data on each grid point is determined by using the incidence angle data corresponding to the extreme value. In fig. 2, which is a cross-hatched area of 1589 line 1825 CRP angle gather, the destination layer is between 2150ms and 2170ms of two-way reflection time, the reflection amplitude of the gather horizon data increases with the increase of the incident angle and shows the AVO characteristic, that is, the amplitude tends to increase with the incident angle, the extreme point on the fitted curve is determined by establishing the fitted curve of the amplitude-incident angle data point of the gather horizon data, and the critical incident angle of the gather is determined by the extreme point; if the critical angle of incidence determined by the extreme point is greater than 30 deg., then the critical angle of incidence for the gather is set to 30 deg.. The critical incident angle of the CRP angle gather at the extreme point on the fitted curve and the AVO characteristic of the extreme point is determined to be 20.25 degrees.
And carrying out gridding interpolation and filtering smoothing processing on the critical incidence angle value data of each CRP point on a 20-line X20-path of the calculation grid by using a minimum flat method on a plane, and interpolating to a 1-line X1-path, thereby obtaining the critical incidence angle plane data of each CRP point. The plane data is used for eliminating angle gathers of all CRP points, gather data larger than a critical incidence angle are kicked to obtain a processed CRP angle gather reconstruction data body, the gather reconstruction data body is used for performing subsequent prestack inversion, for example, the gather reconstruction data body is used for setting three incidence angle range division and superposition to obtain a related data body, and then the three data bodies are used for performing prestack wave impedance inversion, amplitude attribute extraction and other calculations. In the example, data traces for CRP angle gathers greater than 20.25 ° incident angles for a line 1751 trace in fig. 2 are all kicked out, i.e., data traces between 20.25 ° and 33 ° are rejected. Subsequent incidence angle range division processing is carried out on the processed trace set reconstruction data body, and the incidence angle range division is 3-12 degrees, 12-21 degrees and 21-30 degrees; and the divided gather data are superposed to obtain three incident angle data, as shown in fig. 3. And finally, performing subsequent pre-stack or post-stack inversion or correlation attribute calculation by using the three incidence angle data.
The data adopting the technology of the invention is subjected to AVO inversion, and the obtained result is superior to the conventional AVO inversion which uses the data with fixed critical angle for input; and secondly, the results obtained by stacking the gather reconstruction data volume are better than the results obtained by fully stacked seismic data in performance or attribute extraction. The inversion or attribute results obtained by the method are more consistent with the results of geological and well drilling data, and the method is proved to be effective.
FIG. 4 illustrates an electronic device (e.g., a computer server with program execution functionality) including at least one processor, a power source, and a memory and input-output interface communicatively coupled to the at least one processor, according to an exemplary embodiment of the invention; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method disclosed in any one of the preceding embodiments; the input and output interface can comprise a display, a keyboard, a mouse and a USB interface and is used for inputting and outputting data; the power supply is used for supplying electric energy to the electronic equipment.
Those skilled in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer-readable storage medium, and when executed, executes the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
When the integrated unit of the present invention is implemented in the form of a software functional unit and sold or used as a separate product, it may also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: various media that can store program code, such as removable storage devices, ROMs, magnetic or optical disks, etc.
The above description is intended to be illustrative of the present invention and is not intended to be limiting. Various alterations, modifications and improvements will occur to those skilled in the art without departing from the spirit and scope of the invention.
Claims (6)
1. A method for CRP gather data volume reconstruction comprising the steps of:
designing a computational grid, and obtaining critical incidence angle data of each CRP point on the grid point;
the first step comprises the following steps:
a. carrying out corresponding calculation grid design on the research area;
b. converting the CRP gather data subjected to dynamic correction into an angle domain to obtain CRP angle gather data, and performing superposition processing on the CRP angle gather data with an incidence angle within an incidence angle threshold range to obtain a superposition data body;
c. performing well-seismic calibration on the stacked data volume by using well logging data and geological stratification data on the well, determining a top interface and a bottom interface of a target layer, selecting the top interface or the bottom interface as seed points, and performing automatic horizon tracking by using the stacked data volume to obtain horizon data;
d. projecting the horizon data on the calculated grid points onto a CRP angle gather, and performing horizon tracking on the angle gather to obtain gather horizon data of the CRP angle gather;
e. determining a relevant critical incidence angle data value for the angle gather of each CRP point by using the gather horizon data;
step two, carrying out interpolation and smoothing treatment on the critical incident angle data of each CRP point to obtain critical incident angle plane data related to a top interface or a bottom interface of a target layer;
and step three, removing the gather data of which the angle gather of each CRP point is larger than the corresponding critical incident angle by using the critical incident angle plane data of each CRP point to obtain a gather reconstruction data volume.
2. The method of claim 1 wherein said step three further comprises performing prestack inversion, poststack property extraction using said gather reconstruction data volume.
3. The method of claim 1 wherein the threshold range of incidence angles is less than or equal to 30 degrees.
4. The method of claim 3, wherein the critical angle of incidence is determined by:
and establishing a fitting relation curve of a series of amplitude-incidence angle data points on the angle gather horizon data at the CRP point, wherein the incidence angle data corresponding to the extreme point on the fitting curve is the critical incidence angle.
5. The method of claim 4, wherein if the critical angle of incidence determined by the extreme point is greater than 30 degrees, then setting the critical angle of incidence to 30 degrees.
6. An electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 5.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006088729A2 (en) * | 2005-02-12 | 2006-08-24 | Chevron U.S.A. Inc. | Method and aparatus for true relative amplitude correction of seismic data for normal moveout stretch effects |
| CN102736109A (en) * | 2012-06-08 | 2012-10-17 | 中国石油大学(华东) | Method for de-noising, correcting and superposing CRP (Common Reflection Point) gather |
| CN102841375A (en) * | 2012-09-06 | 2012-12-26 | 中国石油大学(华东) | Method for tomography velocity inversion based on angle domain common imaging gathers under complicated condition |
| CN103616723A (en) * | 2013-12-11 | 2014-03-05 | 成都晶石石油科技有限公司 | Amplitude versus offset (AVO) characteristic-based common reflection point (CRP) gather true amplitude recovery method |
| WO2017024702A1 (en) * | 2015-08-11 | 2017-02-16 | 深圳朝伟达科技有限公司 | Inversion system for ray elastic parameter |
| CN109975866A (en) * | 2019-03-20 | 2019-07-05 | 中国石油化工股份有限公司 | A kind of thin reservoir seismic prediction method based on frequency dividing trace gather |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9702999B2 (en) * | 2014-10-17 | 2017-07-11 | Chevron U.S.A. Inc. | System and method for velocity analysis in the presence of critical reflections |
| CA2961572C (en) * | 2014-10-20 | 2019-07-02 | Exxonmobil Upstream Research Company | Velocity tomography using property scans |
| US11169293B2 (en) * | 2016-12-13 | 2021-11-09 | Cgg Services Sas | Device and method for model-based deblending |
-
2019
- 2019-08-13 CN CN201910745649.9A patent/CN112394393B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006088729A2 (en) * | 2005-02-12 | 2006-08-24 | Chevron U.S.A. Inc. | Method and aparatus for true relative amplitude correction of seismic data for normal moveout stretch effects |
| CN102736109A (en) * | 2012-06-08 | 2012-10-17 | 中国石油大学(华东) | Method for de-noising, correcting and superposing CRP (Common Reflection Point) gather |
| CN102841375A (en) * | 2012-09-06 | 2012-12-26 | 中国石油大学(华东) | Method for tomography velocity inversion based on angle domain common imaging gathers under complicated condition |
| CN103616723A (en) * | 2013-12-11 | 2014-03-05 | 成都晶石石油科技有限公司 | Amplitude versus offset (AVO) characteristic-based common reflection point (CRP) gather true amplitude recovery method |
| WO2017024702A1 (en) * | 2015-08-11 | 2017-02-16 | 深圳朝伟达科技有限公司 | Inversion system for ray elastic parameter |
| CN109975866A (en) * | 2019-03-20 | 2019-07-05 | 中国石油化工股份有限公司 | A kind of thin reservoir seismic prediction method based on frequency dividing trace gather |
Non-Patent Citations (3)
| Title |
|---|
| CRP道集优化处理对叠前反演的影响;鲍熙杰等;《石油地质与工程》;第27卷(第01期);第39-41、55页 * |
| 基于CRP道集优化处理的叠前AVA同步反演技术的应用――以KL9构造区为例;邓吉锋等;《石油物探》;第58卷(第03期);第461-470页 * |
| 高速灰岩屏蔽层下伏储层预测技术组合研究与应用;刘志斌等;《中国海上油气》;第30卷(第06期);第51-61页 * |
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