CN111399048A - Method for calculating correlation attribute and data weighted reconstruction of broken solution - Google Patents

Method for calculating correlation attribute and data weighted reconstruction of broken solution Download PDF

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CN111399048A
CN111399048A CN202010355200.4A CN202010355200A CN111399048A CN 111399048 A CN111399048 A CN 111399048A CN 202010355200 A CN202010355200 A CN 202010355200A CN 111399048 A CN111399048 A CN 111399048A
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蒋裕强
蒋增政
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Sichuan Jierui Taike Technology Co ltd
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Abstract

The invention discloses a method for calculating relevant attributes and performing weighted reconstruction on data of an interrupted solvent, which at least comprises the following steps: s1: determining a data value of a broken central angle in a research area, setting an azimuth angle range parameter, and performing superposition and offset processing on a related central angle gather data volume to obtain a related central angle data volume; s2: calculating attribute data volumes related to faults for the central angle data volumes, and performing attribute calculation aiming at the karst cave by using the related seismic data volumes to obtain attribute data volumes related to karst cave response; s3: and after normalization processing is carried out on each attribute data volume, a reconstructed data volume for analysis of the solution breaking is obtained through data weighting reconstruction. By the method, accurate imaging work of the solution breaking system and the like in a research area is realized, the position prediction precision of geological abnormal bodies in related exploration areas is improved, drilling risks are reduced, and the economic benefit of oil-gas exploration of the solution breaking system is improved.

Description

Method for calculating correlation attribute and data weighted reconstruction of broken solution
Technical Field
The invention belongs to the field of petroleum and gas exploration, and particularly relates to a method for calculating relevant attributes and performing weighted reconstruction on data of an episodic solute.
Background
In the current stage of oil and gas exploration, the solution breaking body is a geological target body with higher exploration value. In oil and gas exploration, the deep-layer fracturing fluid has a great exploration value, and a well drilled on the fracturing fluid usually obtains high-yield industrial airflow, but a well drilled outside the fracturing fluid usually has no gas or weak gas production.
In addition, in the oil and gas exploration practice, it is found that seismic imaging of stratums and karsts in the solution breaking system needs to be enhanced urgently. In general, the dissolved gas reservoir has extremely strong heterogeneity, the identification of related secondary fractures, the carving of the dissolved gas boundary and the representation of an inner curtain are very difficult, and the problems of unclear visibility, inaccurate drawing and inaccurate printing exist.
Currently, most solution imaging techniques use post-stack seismic data to predict the location of the solution system. As in some solution plane imaging predictions, it is mainly done by extracting the along-layer properties using coherent volume calculations or color fusion, instantaneous amplitude properties, etc. However, the accuracy of imaging of the solution is not high, and there are cases where the imaging is disturbed by karst, fracture anisotropy, and the like.
In the research on the solution breaking, a patent of invention, namely an earthquake recognition method and device for reservoir connectivity of the solution breaking (patent number: CN201810227814.7), discloses that a three-dimensional earthquake data body is used for constructing an earthquake maximum likelihood body, the earthquake maximum likelihood body is subjected to space carving by using a threshold value of the attribute of the earthquake maximum likelihood body to obtain a space profile of the solution breaking, a first point and a second point which are positioned at the same altitude are selected in the space of the solution breaking, the formation pressure at the first point and the formation pressure at the second point are obtained, the formation pressure at the first point and the formation pressure at the second point are compared, and whether the reservoirs between the first point and the second point are communicated or not is judged according to the comparison result.
The patent of the invention, namely a representation method of an internal structure of a fractured carbonate rock fluid (patent number: CN201710595771.3), provides a method for inverting seismic data after superposition to obtain underground wave impedance data, determines a wave impedance data threshold value representing the development of a fracture-cavity type reservoir body, carries out hollowed carving processing on the underground wave impedance data according to the wave impedance data threshold value, calculates tensor attributes of the seismic data, carries out spatial smoothing processing on the tensor attributes, determines a tensor attribute threshold value representing a fractured fluid fracture area, processes the tensor attribute spatial smoothing processing result according to the tensor attribute threshold value to obtain the profile of the fractured fluid, and displays the tensor attributes and the underground wave impedance data in the profile by taking the profile of the fractured fluid as a boundary to realize the external profile carving and the internal structure representation of the fractured fluid.
At present, the conventional seismic technology is utilized to carry out the related research results in the aspect of plane prediction of geological abnormal bodies such as solution bodies and the like at home and abroad, but the prediction effects are relatively poor and satisfactory, and the conventional geological, well logging and seismic knowledge is combined, so that the following problems are considered to exist mainly:
(1) the imaging technology of the conventional dissolved geological anomalous body generally uses post-stack seismic data for calculation, and the seismic response of the fault layer of some dissolved geological anomalous bodies is usually suppressed due to the fact that the omni-directional angle stack of the conventional seismic data has an average effect;
(2) when the single attribute is used for describing the karst, the karst and the fracture cannot be accurately and effectively considered, so that the related describing result is inaccurate.
Disclosure of Invention
The invention aims to solve the problems in the imaging technology of the conventional seismic data on geological abnormal bodies such as the solution body and the like, discloses a method for calculating relevant attributes and performing data weighted reconstruction on the solution body, can realize accurate imaging work on the solution body breaking system and the like in a research area, improves the position prediction precision of the geological abnormal bodies in a relevant exploration area, further reduces the drilling risk and improves the economic benefit of oil-gas exploration of the solution body breaking system.
The purpose of the invention is realized by the following technical scheme:
a method for computing correlation properties and data weighted reconstruction of an episolve, the method comprising at least the steps of:
s1: determining a data value of a broken central angle in a research area, setting an azimuth angle range parameter, and performing superposition and offset processing on a related central angle gather data volume to obtain a related central angle data volume; s2: calculating attribute data volumes related to faults for the central angle data volumes, and performing attribute calculation aiming at the karst cave by using the related seismic data volumes to obtain attribute data volumes related to karst cave response; s3: and after normalization processing is carried out on each attribute data volume, a reconstructed data volume for analysis of the solution breaking is obtained through data weighting reconstruction.
According to a preferred embodiment, the step S1 specifically includes: s11: calculating the fracture trend of the research area, and determining the data value of the central angle of the fracture according to the fracture trend; s12: and determining the azimuth angle range of the central angle, and performing superposition and offset processing on the related central angle gather data volume to obtain the related central angle data volume.
According to a preferred embodiment, the zone of interest fractures run in the north direction at 0 ° and the meter is rotated in the clockwise direction by 360 °.
According to a preferred embodiment, the trend of the region of interest fracture is obtained by extracting relevant attribute slices from the target layer or performing structural stress field analysis based on geological data.
According to a preferred embodiment, the central angular direction takes an angular value of a direction at 90 ° to the fracture strike.
According to a preferred embodiment, the seismic data volume in step S2 is an omnidirectional pre-stack or post-stack seismic data volume.
The main scheme and the further selection schemes can be freely combined to form a plurality of schemes which are all adopted and claimed by the invention; in the invention, the selection (each non-conflict selection) and other selections can be freely combined. The skilled person in the art can understand that there are many combinations, which are all the technical solutions to be protected by the present invention, according to the prior art and the common general knowledge after understanding the scheme of the present invention, and the technical solutions are not exhaustive herein.
The invention has the beneficial effects that:
the method can complete the precise imaging of the dissolution breaking system of the target layer in the time domain, and determine the accurate position of the dissolution breaking body on a plane and a three-dimensional space, thereby reducing the drilling risk and improving the exploration benefit of the dissolution breaking body oil gas. The method can be popularized to other prediction aspects of geological abnormal bodies, such as prediction of linear reef phases, rock solutions, linearly distributed volcano imaging and the like.
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FIG. 1 is a schematic flow diagram of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that, in order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments.
Thus, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention discloses a method for computing correlation attributes and data weighted reconstruction of an interrupted solvent, the method at least comprises the following steps:
s1: determining a data value of a broken central angle in a research area, setting an azimuth angle range parameter, and performing superposition and offset processing on a related central angle gather data volume to obtain a related central angle data volume;
s2: calculating an attribute data volume which is relatively sensitive to fault response for the central angle data volume, and performing attribute calculation aiming at the karst cave by using the related seismic data volume to obtain an attribute data volume related to the karst cave response;
s3: and after normalization processing is carried out on each attribute data volume, a reconstructed data volume for analysis of the solution breaking is obtained through data weighting reconstruction.
The invention is further described below with reference to the figures and examples.
Designing a central angle data value perpendicular to the fracture trend and a related optimal azimuth angle range for a research area, and calculating a related central angle data body; secondly, calculating an attribute data volume with better response to the karst and the fracture according to the seismic data volume and the test result of the related technical method; and after normalization processing is carried out on each attribute data volume, weighting reconstruction processing is carried out to obtain a reconstructed data volume for analysis of the solution breaking. The aim of precisely predicting the position of the solution in the research area by using the seismic technology can be achieved by slicing the data volume along the layer or displaying the data volume in a three-dimensional way aiming at the target layer.
As can be seen from fig. 1, the present invention comprises the following steps:
and step S1, determining the data value of the broken central angle in the research area, setting azimuth angle range parameters, and performing superposition and offset processing on the related central angle gather data volume to obtain the related central angle data volume.
Step S11: the fracture strike is calculated for the entire study area and the fracture center angle data value is determined from the strike.
Wherein, the trend of the fracture is that the true north direction is 0 degree, the clockwise rotation is counted to 360 degrees. Based on the symmetry principle, the fracture trend is converted from the azimuth of 0-360 degrees to the azimuth of 0-180 degrees.
Fracture trends in the region of interest can be obtained from geological data, by extracting relevant property slices from the target zone, or by performing tectonic stress field analysis on the slices.
And taking the trend which is 90 degrees or large-angle intersection (greater than or equal to 80 degrees) with the fracture trend as a central angle data value according to the fracture trend. I.e., the direction of the central angle intersects the fault strike at a normal or large angle (greater than or equal to 80 °), and so on, to complete the determination of the central angle data value for the associated fracture.
Step S12: and determining the optimal azimuth angle range of the central angle, and performing superposition and offset processing on the related central angle gather data volume to obtain the related central angle data volume.
Step S12 is to test the azimuth data values set symmetrically about the center angle to determine the best azimuth data value.
The specific azimuth angle range test mainly uses the central angle of a sample grid point (CDP) as the center, and superposes the trace set data (all incident angles) in the azimuth angle range obtained by simultaneously increasing or decreasing 1 degree in the positive and negative 12 degrees range, and when the reflection amplitude of the relevant fault of the superposed trace is maximum or the corresponding azimuth angle range is relatively clear, the azimuth angle range is used as the optimal azimuth angle parameter of the central angle type. And the analogy is repeated to complete the determination of the optimal azimuth angle parameter of each central angle.
And overlapping and offsetting the gather data volume of the relevant azimuth angle range by using the determined central angle and the azimuth angle range thereof to obtain the relevant central angle data volume. The sample grid points (CDP) are points known to be on the target layer faults and are representative of amplitude anomalies caused by the faults to be reflected. Preferably, the gather is a dynamically corrected gather data volume which is subjected to pre-stack denoising, amplitude compensation, signal-to-noise ratio improvement, relevant static correction and the like; the data volume of the gather of the azimuth angle range is that data tracks in a certain azimuth angle range are reserved, and the data tracks outside the azimuth angle range are all set to be zero or cut off, so that the data tracks do not participate in subsequent superposition and offset processing. Alternatively, the azimuth gather may be subjected to the prestack time migration processing and then to the superimposition processing to obtain the post-stack data volume. Specifically, the method of stacking and shifting should be determined according to the actual situation, the expert experience, the imaging precision of the fracture, and the like.
The dividing parameters of the related azimuth angle range are as follows:
σi＝βi+ΔΦ+10° (1)
σj＝βi-ΔΦ-10° (2)
in the formulas (1) and (2), σ i is the maximum azimuth value of the ith central angle, σ j is the minimum azimuth value of the ith central angle, β i is the central angle data value of the ith central angle, Δ Φ is the azimuth increment and is 1 °, 2 °, … 9 °, or-1 °, -2 °, … -9 °, if the central angle value is less than 12 °, the central angle data value is used as 12 ° to calculate the azimuth angle range, and if the central angle value is [168 °, 180 ° ]]In this case, it is regarded as 165°The calculation of the azimuth angle range is performed by performing the central angle data value. σ i and σ j constitute the test azimuth range for the ith central angle.
Wherein, the azimuth gather sets the north direction as 0 by setting the observation system direction in the seismic data processing°Clockwise rotation, meter 360°. Based on the symmetrical principle of excitation and reception, the seismic data shot point-wave detection point 360 acquired in the field is processed°Orientation conversion to 180°An azimuth angle. Thus, the azimuth angle of the concentration of the track is converted into [0 °, 180 °]。
Step S2: and calculating an attribute data volume which is relatively sensitive to fault response for the central angle data volume, and performing attribute calculation aiming at the karst cave by using the related seismic data volume to obtain the attribute data volume related to the karst cave response. The method specifically comprises the following steps:
step S21: attribute data volumes relating to the fault are calculated for each central angle data volume.
The main operation is to optimize one of the attribute data bodies to go to the next step according to the result of the calculation attribute of the correlation and fracture analysis. Typically, a small test area is established within the study area as a test for the technical methods and parameters for calculating relevant fracture properties. The specific operation is that according to the response of the relevant central angle data volume to the corresponding fracture, various algorithms and parameter tests relevant to the fracture response attribute are carried out, and the technical method and the parameters corresponding to the attribute with better fracture imaging effect (high definition) are optimized to enter the next step. And the like, and the determination of the method and the parameters of each central angle data body for calculating the fracture attribute is completed. Then, by using related technical methods and parameters, each central angle data body is taken as an input, so that an attribute data body with relatively sensitive fault response is obtained.
In practice, the same technical method for calculating fracture properties may be used to calculate each central angle data volume. In general, the calculation method of the correlation with respect to the lysosome includes an amplitude change rate, an energy body technique, coherence, ant body and tensor properties, wave impedance properties, and the like. In actual operation, it can be determined which technique or combination of techniques is used to calculate the related attribute data according to expert experience, fracture calculation accuracy, actual data, and the like.
Some of the methods related to the calculation for fracture properties are as follows:
(a) and (3) a coherent computing method. The coherent algorithm C2 is mainly used for coherent body calculation of the three-dimensional post-stack seismic data body. In the process of using the C2 coherent body algorithm to perform coherent body calculation on the three-dimensional post-stack data volume, firstly, the apparent dip angles p and q of the central point in the analysis time window in the C2 coherent algorithm in the x direction and the y direction of the local reflection surface are correspondingly tested, and the parameter test is best to achieve the purpose of clearly describing the larger-scale fracture or karst form on the plane in the test area (the test area is only a small block in the research area). And after the test is finished, performing coherent body calculation on the post-stack data bodies of all the central angles by using the view dip angles p and q determined by the test.
The C2 coherent body algorithm mainly defines a rectangular or elliptical analysis time window centered on an analysis point and containing J traces of seismic data, and uses the local coordinate axis as the center of the analysis point, so that the similarity coefficient σ (t, p, q) can be calculated according to the following expression:
Figure BDA0002473194250000061
wherein the content of the first and second substances,the subscript j denotes the jth trace, x, falling within the analysis windowjAnd yjRespectively representing the distances between the jth track and a central point t in an analysis time window in the x direction and the y direction, K representing a vertical analysis time window, H representing Hilbert transform, p and q respectively representing the apparent dip angles of a local reflection interface in the analysis time window in the x direction and the y direction of the central point t, and ujRepresenting the seismic data of the jth trace in the analysis time window.
According to the expression (3), the inclination direction of the local plane can be adjusted by changing the values of the apparent inclination angles p and q, so that a similarity coefficient is correspondingly obtained. By searching the maximum similarity coefficient, the local plane can achieve the best fit with the actual reflection interface, and therefore the pixel coefficient at this time is also the coherence estimation value (i.e. coherence data value) of the analysis point.
It should be noted that in other embodiments of the present invention, the method may also use other reasonable algorithms (for example, C1 coherent algorithm, C3 coherent algorithm, or new generation coherent algorithm) to perform coherent body calculation on the stacked seismic data volume in step 1, and the present invention is not limited thereto.
(b) The computation of the fracture also has a maximum likelihood (L ikeihood) attribute that favors suppressing disturbances that are not fractures, thereby highlighting the response of the fracture. L ikeihood attribute is based on the seismic similarity attribute, so the similarity attribute is first computed before computing L ikeihood attribute.conventional similarity attributes are the contrast relationships of seismic reflection features (waveform, amplitude, phase, etc.) between adjacent traces, and for suppressing the imaging of noisy prominent fractures, Hale proposed in 2013 a Semblance (numerical range 0-1) of similarity attribute oriented with prominent fracture recognition, with the following specific formula:
Figure BDA0002473194250000071
wherein g is a three-dimensional seismic data body, s represents that the seismic data body in brackets is subjected to structure-oriented smoothing, f represents that filtering is carried out again along the trend and the inclination direction of the fracture, and the filtering is mainly used for enhancing the stability of Semblance attribute calculation, and the calculation formula of L Ikelihood attribute is as follows:
Likelihood＝1－Semblance8(5)
it can be seen that the L ikelihood attribute is the difference between the exponential power of the Semblance attribute and 1, and is limited to a value in the range of 0-1 compared to the Semblance attribute, the L ikelihood attribute has a magnifying effect on the contrast relationship of similarity between neighboring spots, and is more conducive to highlighting the imaging of fractures.
According to the formula, L ikelihood attributes can also be understood as the probability of fracture development at sampling points, the more continuous the seismic event, the larger the Semblance attribute is, the smaller the L ikelihood attribute is, i.e. the probability of fracture development is, the lower the continuity of the seismic event at the breakpoint position is, the smaller the Semblance attribute is, the greater the L ikelihood attribute is, i.e. the probability of fracture is increased.
In addition, the central angle data volume may be subjected to frequency division processing or other data fusion processing, and then correlation attributes may be calculated to highlight the response of fracture. Specifically, what kind of technical method is used to participate in the attribute calculation for the fracture should be determined according to the seismic data, the expert experience, the comparison of the related test results, and the like.
Step S22: and performing attribute calculation aiming at the karst cave by using the related seismic data volume, and obtaining an attribute data volume about karst cave response. The seismic data volume can be an all-dimensional pre-stack or post-stack seismic data volume, and the corresponding calculation method also has various responses capable of reflecting the karst cave. Therefore, with reference to the testing method in step 21, the relevant data volume and the attribute reflecting the cavernous body obtained by calculation thereof are optimized, and the attribute reflecting the form and position of the cavernous body can be selected relatively clearly. Secondly, by using the technical method and parameters corresponding to the attribute, the related data volume is used as input, and the attribute data volume reflecting the karst cave response is obtained after the related calculation. In general, the post-stack seismic data volume can be utilized, and the amplitude change rate calculation method based on the structure guidance is utilized to implement the calculation of the related attributes, and the attributes can also better reflect the karst cave form; of course, prestack gather data can be used for prestack AVO inversion, elastic wave inversion and the like, and a gradient data body or a Poisson ratio data body can be calculated, so that the data can have better response to the form of the related karst cave.
Step S3: and after normalization processing is carried out on each attribute data volume, a reconstructed data volume for analysis of the solution breaking is obtained through data weighting reconstruction. The method specifically comprises the following steps:
and setting a relevant optimal weighting factor for each normalized attribute data volume, and performing data weighting reconstruction processing on each attribute data volume by using the relevant optimal weighting factor to obtain a reconstructed data volume for analyzing the dissolved solutions. The normalization processing is a dimensionless processing means, which changes the absolute value of the physical system value into a certain relative value relation, i.e. the normalization processing uses addition, subtraction, multiplication, division or the combination of the addition, the subtraction, the multiplication and the division to operate; the normalization process is to set the sample data as Xp(P ═ 1, 2, …, P), definition of xmax＝max{Xp}，xmin＝min{xpAnd converting the sample data into data in an n-m interval by normalization processing calculation, wherein the normalization processing calculation formula is as follows:
Figure BDA0002473194250000081
in the formula (6), XpTo normalize the pre-processed sample values, XpiTo normalize the processed sample values, xmax＝max{Xp}，xmin＝min{xpN and m are positive integers, m>n≥0。
The main operation of the data weighted reconstruction is as follows:
(a) and determining the related optimal weighting factor ki of each attribute data volume reconstruction. The value can be correspondingly designed and tested and evaluated by an equivalence method or a non-equivalence method, the large value of the weighting factor can be properly inclined to the data volume of the attribute of the fracture body in the design, and then the better weighting factor can be evaluated by utilizing the calculation and analysis of the evaluation factor, wherein the value is determined according to the corresponding seismic data and the target geologic body. One attribute data body corresponds to one weighting factor in one data reconstruction, different weighting factor circulation tests can be carried out, and finally the factor which is optimal in each data combination is preferably selected.
The detailed calculation formula of the weighting factor is as follows:
1. and (3) an equivalence method: the weighting factors are equal or approximately consistent, and the calculation formula is as follows:
Figure BDA0002473194250000082
Figure BDA0002473194250000083
in the above formula kiIs the weighting factor of the ith weighted data volume and n is the number of weighted data volumes.
2. Non-equivalent method: calculating by adopting the normalized attribute value of each attribute data at a sampling karst or a fracture point, wherein the weighting factor design principle is that the boundary of a target geologic body to be predicted is mainly and optimally highlighted, and the calculation formula is as follows:
Figure BDA0002473194250000084
Figure BDA0002473194250000085
Figure BDA0002473194250000091
where ki is the weighting factor for the ith attribute data volume, AiFor the normalized attribute value of the attribute data body on the sampling rock solution point or the fracture point after the data weighting reconstruction, A/ iFor the normalized attribute value of the ith weighted data body at the sampling rock solution point or fracture point, n is the number of weighted data bodies。
(b) The weighting factor can be evaluated by evaluating the evaluation factor. Since the weighted effect is mainly to highlight the medium and small scale karst and fracture morphology. The specific implementation of the effect evaluation is that after normalization processing is respectively carried out on a test reconstruction data body and a post-stack coherent data body (as a comparison test data body), data values of medium and small scale solution breaking test areas are extracted according to n sampling points, mathematical operation is carried out on the data values and the small scale solution breaking test areas, and an evaluation factor is obtained, wherein the smaller the evaluation factor is, the better the reconstruction effect is. The weighting factor and the evaluation factor have a causal relationship, a group of designed weighting factors are firstly used, and then the evaluation factor is obtained after data reconstruction is carried out by using the factors. Thus, a set of weighting factors corresponds to an evaluation factor. The corresponding evaluation factors are obtained from the weighting factors of different groups, and actually, the process of performing feedback evaluation on the plurality of groups of weighting factors and continuously performing cyclic evaluation to obtain the relatively optimal weighting factor is performed. The evaluation factor is calculated as follows:
Figure BDA0002473194250000092
n≥2 (13)
in the above formula
Figure BDA0002473194250000093
To evaluate the factor, MiReconstructing the normalized data value, M ^ based on the target geologic volume of the data volume for the ith pointiThe normalized data value of the target geologic body of the ith point post-stack coherent data volume is used, n is the number of all sampling points in a part of data volume used for testing and calculation, the part of data volume is called a testing data volume, and the selection principle of the part of data volume should contain the different development scale of the lysis solutions as much as possible. It is generally considered that
Figure BDA0002473194250000094
Then it is good; when in use
Figure BDA0002473194250000095
Good results are obtained; when in use
Figure BDA0002473194250000096
It is superior. In general, MiThe normalized attribute data value of (1) is an attribute average value of a target geologic interval, and the target geologic interval is a two-pass reflection time period containing a solution.
(c) And performing data reconstruction on the related attribute data volume by using the optimal weighting factor to obtain a reconstructed data volume, wherein a data reconstruction calculation formula is as follows:
Figure BDA0002473194250000097
in formula (14): y is a reconstructed data body after weighted data processing; ciIs the ith weighted attribute data volume; where ki is the optimal weighting factor for the ith weighted attribute data volume,
Figure BDA0002473194250000098
and 0 ≦ ki。
The method of the invention sets a central angle and an optimal azimuth angle range related to the fracture trend, and calculates a related central angle data body; secondly, calculating an attribute data volume with better response to the karst and the fracture according to the related seismic data volume and the test result of the related technical method; and after normalization processing is carried out on each attribute data volume, data weighting reconstruction processing is carried out according to the respective optimal weighting factors, and a reconstruction data volume for analysis of the solution breaking is obtained. The aim of precisely predicting the position of the solution in the research area by using the seismic technology can be achieved by slicing the data volume along the layer or displaying the data volume in a three-dimensional way aiming at the target layer.
The embodiment of the invention is as follows:
referring to fig. 1, according to the technical process of the method, working steps are formulated, and the example is to accurately position a dissolving system of a certain three-dimensional work area, so that a foundation is laid for subsequent oil and gas exploration.
In step S1, the research results related to the research area are analyzed, and it is found that the target layer is mainly fractured in two directions, i.e., north east direction and near east west direction. The imaging analysis of the fractured-solvent system shows that the fracture imaging of the research area is relatively poor, the fracture morphology is not very clear, and the rock-solvent is relatively clear and forms interference on the imaging of the fractured system. Therefore, it is necessary to reprocess the relevant seismic data, so that the morphology of the solution fracture can be enhanced and the hydrocarbon-containing characteristics of the solution fracture can be researched after the solution fracture is calculated by the relevant technology.
In the step, firstly, the top of a target interval is determined by using seismic data, logging data, geological stratification data and the like, and after the layer position is explained, interpolation and smoothing are carried out, the layer position data of 1 line X1 is obtained. And according to the trend of fracture, determining two central angle data values, namely 130 degrees (for the central angle data value of the northeast fracture) and 12 degrees (for the central angle data value of the nearly east fracture), determining the optimal azimuth angle range of the two central angles to be +/-12 degrees after a correlation test, and performing superposition and offset processing on the two central angle trace set data bodies by using the correlation central angle and the optimal azimuth angle range parameters to obtain two central angle data bodies.
In step S2, the two central angle data volumes are subjected to related calculation techniques and parameter tests for fracture attributes, from which the maximum likelihood attribute is selected for proceeding to the next step. In actual operation, the maximum likelihood attribute calculation is carried out on the two central angle data bodies by using the related maximum likelihood attribute calculation method and parameters to obtain two attribute data bodies. In actual operation, aiming at the karst aspect, the calculation of karst detection is mainly implemented by using a post-stack seismic data volume and an amplitude change rate calculation method, so that an amplitude change rate data volume is obtained.
In step S3, normalization calculation is performed using the maximum likelihood attribute data volumes of two central angles and one amplitude change rate attribute data volume, and the correlation data value is classified into the (12, 100) value domain. And carrying out weighting factor test on the three attribute data bodies (the test data body adopts a normalized coherent data body and belongs to a (12, 100) value domain) to obtain related optimal weighting factors. After the relevant tests, the weighting factors used were 0.41 (normalized data volume calculated for northeast fracture), 0.35 (normalized data volume calculated for eastern and westward fracture), and 0.24 (data volume calculated for karst), respectively. And performing weighted data fusion calculation on the related attribute data volume by adopting a related optimal weighted factor to obtain a reconstructed data volume for analyzing the solution breaking.
The reconstructed data volume obtained by the technology is superior to the conventional post-stack coherent data volume in the aspect of solution breaking imaging and obtains related obvious geological results by analyzing the reconstructed data volume and the related conventional post-stack coherent data volume on the section.
The above-described embodiment is only one embodiment of the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be easily made based on the application and principle of the present invention disclosed in the present application, and the present invention is not limited to the method described in the above-described embodiment of the present invention, so that the above-described embodiment is only preferred, and not restrictive.

Claims (6)

1. A method for computing correlation properties and data weighted reconstruction of an episolve, the method comprising at least the steps of:
s1: determining a data value of a broken central angle in a research area, setting an azimuth angle range parameter, and performing superposition and offset processing on a related central angle gather data volume to obtain a related central angle data volume;
s2: calculating attribute data volumes related to faults for the central angle data volumes, and performing attribute calculation aiming at the karst cave by using the related seismic data volumes to obtain attribute data volumes related to karst cave response;
s3: and after normalization processing is carried out on each attribute data volume, a reconstructed data volume for analysis of the solution breaking is obtained through data weighting reconstruction.
2. The method according to claim 1, wherein the step S1 specifically includes:
s11: calculating the fracture trend of the research area, and determining the data value of the central angle of the fracture according to the fracture trend;
s12: and determining the azimuth angle range of the central angle, and performing superposition and offset processing on the related central angle gather data volume to obtain the related central angle data volume.
3. The method of claim 2, wherein the fracture of the study area is oriented with true north at 0 ° and the meter is rotated clockwise at 360 °.
4. The method for computing correlation properties and data weighted reconstruction of the solution according to claim 3, wherein the trend of the region of interest fracture is obtained by slicing the correlation properties of the target layer or performing structural stress field analysis based on geological data.
5. The method of claim 4, wherein the central angular direction is an angular value of a direction 90 ° from the fracture strike.
6. The method for computing correlation properties and data weighted reconstruction for an interrupted solution according to claim 1, wherein the seismic data volume in step S2 is an omnidirectional pre-stack or post-stack seismic data volume.
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