A multi-well elastic parameter consistency correction method considering the influence of depth compaction

Abstract

This disclosure provides a method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction. The method includes: determining a standard layer within the correction area; obtaining regional correlation by statistically analyzing and trend-fitting the acoustic, density, resistivity, and natural gamma curve data within the standard layer segment; performing histogram correction on the differences generated by the regional correlation; and backfilling the corrected differences to complete the consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction. Based on depth trend analysis, this method transforms the original single-point and two-point histogram methods into a depth trend method. This not only improves the problem of histogram correction altering the original well attributes but also solves the problem of "bull's-eye" phenomena in inversion results caused by correction results that do not consider the compaction depth trend. This method can effectively improve reservoir prediction accuracy and has significant application value in the field of oil and gas field exploration.

Description

Technical Field

[0001] This disclosure relates to the field of geophysical technology, specifically to a method for consistency correction of elastic parameters in multiple wells that takes into account the influence of burial depth and compaction. Background Technology

[0002] The statements in this section provide only background information in connection with this disclosure and do not constitute prior art.

[0003] Well logging curves can indirectly reflect the lithological information of the subsurface medium. Detailed analysis of well logging interpretation results can directly guide seismic inversion reservoir prediction. In practice, well logging data is affected by factors such as instrumentation, acquisition age, and mud invasion. Therefore, for all exploration wells within a specific work area, consistency correction of elastic parameters across multiple wells is often required.

[0004] Currently, the main method for consistency correction of elastic parameters in multi-well systems is the histogram method, which can be further divided into single-point and two-point methods. However, the histogram correction method for well logging curves has the following shortcomings: 1. The histogram correction method requires that the distribution pattern of the selected standard wells be consistent with the regional geological characteristics. If they are inconsistent, it will modify the original attributes of some wells, making the results inaccurate; 2. Density and sonic velocity usually change with different burial depths. The density and sonic velocity values ​​within the same layer are often affected by the structural depth. The histogram correction method does not consider the influence of the compaction trend at burial depth. Therefore, using this data for seismic inversion reservoir prediction will lead to the "bull's eye" phenomenon in the inversion results.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art. Summary of the Invention

[0006] In view of this, this disclosure provides a multi-well elastic parameter consistency correction method that considers the influence of burial depth and compaction, which solves the problems of the histogram method correction method changing the original attributes of the well and failing to consider the influence of burial depth and compaction trend factors, resulting in the "bull's eye" phenomenon in the seismic inversion results.

[0007] To achieve the above-mentioned objectives, the technical approach of the multi-well elastic parameter consistency correction method considering the influence of burial depth compaction described in this invention is as follows:

[0008] By applying depth trend analysis, the consistency correction method for multi-well elastic parameters is transformed from the original single histogram single-point method and two-point method to the depth trend method, thus forming a multi-well elastic parameter consistency correction method that considers the influence of burial depth and compaction, providing effective technical support for guiding seismic inversion reservoir prediction work.

[0009] To achieve the above-mentioned objective, the multi-well elastic parameter consistency correction method considering the influence of burial depth compaction includes:

[0010] Identify the standard layers and reference wells within the calibration area;

[0011] Depth trend analysis was performed on the reference well curve data within the standard layer to obtain regional correlation.

[0012] The differences generated by the regional correlation are corrected by histogram, and the corrected differences are backfilled to complete the consistency correction of the elastic parameters of multiple wells considering the influence of burial depth and compaction.

[0013] In this disclosure and possible embodiments, the method for determining the standard layer and reference well within the correction area includes:

[0014] Within the calibration area, select trend analysis wells and set the standard layers and curve categories for trend analysis. The trend analysis wells include wells that cover the target layer with sonic, density, resistivity, and natural gamma curves.

[0015] After removing anomalies from the trend analysis wells and their logging curves, reference wells are selected according to standard layers. The reference wells are regional standard wells obtained by taking the arithmetic mean of all trend analysis wells after the anomaly removal process.

[0016] In this disclosure and possible embodiments, the method for removing anomalies from the trend analysis well and its logging curves includes:

[0017] Determine whether the logging response characteristics of the target layer are abnormal. If abnormal, decide whether to remove the abnormal value or remove the well based on the formation sedimentary characteristics.

[0018] In this disclosure and possible embodiments, the method for performing depth trend analysis on reference well curve data within the standard layer to obtain regional correlation includes:

[0019] The data for in-depth trend analysis is projected and analyzed in scatter form, and the algorithm for trend fitting is selected.

[0020] The fitting algorithm is a bivariate k-th degree polynomial, and the equation is expressed as follows:

[0021] A0 = c1 + c2x + c3y + c4x 2 +c5xy+c6y 2 +…;

[0022] In the formula: A0 represents the logging response trend value; c i (i = 1, 2, 3, ...) represents non-fixed coefficients; (x, y) represents the horizontal and vertical coordinates of a certain well location;

[0023] The random error between the fitted logging response trend value and the actual surface is expressed as:

[0024] e = A - A0;

[0025] In the formula: A represents the true value, A0 represents the fitted trend value, and e represents the random error;

[0026] The fitting principle is to make the fitted trend value infinitely close to the true value, that is, to make the random error e infinitely close to 0.

[0027] In this disclosure and possible embodiments, determining the regional correlation requires obtaining acoustic, density, resistivity, and natural gamma curve data through well logging techniques.

[0028] In this disclosure and possible embodiments, the method for performing histogram correction processing on the differences generated by the regional correlation, and backfilling the corrected differences to complete the consistency correction of multi-well elastic parameters considering the influence of burial depth and compaction, includes:

[0029] In the aforementioned regional correlation, a histogram is used to project the trend difference, and the regional difference is simultaneously corrected using a histogram. After the histogram-corrected regional difference undergoes consistency processing, the correction amount is backfilled after regional data correction to obtain the deep trend correction result.

[0030] In this disclosure and possible embodiments, the correction method further includes:

[0031] The verification method involves comparing the constructed depth trend surface with the depth trend correction result trend surface. If the constructed trend and the correction result trend are consistent and there is no bullseye phenomenon, it indicates that the correction effect is good. If the two trends are inconsistent, it indicates that there is a problem with the correction result. If the problems with parameters, standard layer selection and logging curve data are excluded, it indicates that the above correction method is not applicable to the corresponding area.

[0032] The beneficial effects of this invention are as follows:

[0033] This disclosed method for consistency correction of elastic parameters in multiple wells, considering the influence of burial depth and compaction, is based on depth trend analysis. It transforms the original single-point and two-point histogram methods into a depth trend method, which not only improves the problem of histogram correction altering the original attributes of wells, but also solves the problem of "bull's-eye" phenomenon in inversion results caused by correction results that do not consider the compaction depth trend. This method can effectively improve the accuracy of reservoir prediction and has great application value in the field of oil and gas field exploration. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0035] Figure 1 This is a schematic diagram illustrating the selection of reference wells and standard layers in an embodiment of this disclosure;

[0036] Figure 2 This is a depth trend analysis chart based on reference well curve data within a standard section;

[0037] Figure 3-1 and Figure 3-2 These are the trend surface constructed at depth and the trend surface corrected by the depth trend analysis method, respectively.

[0038] Figure 4 This is a flowchart of a multi-well elastic parameter consistency correction method that takes into account the influence of burial depth and compaction. Detailed Implementation

[0039] The present disclosure is described below based on embodiments; however, it is worth noting that the present disclosure is not limited to these embodiments. In the detailed description of the present disclosure below, certain specific details are described in detail. However, those skilled in the art will fully understand the present disclosure for the parts not described in detail.

[0040] Furthermore, unless the context explicitly requires it, the words "comprising," "including," and similar terms throughout the specification and claims should be interpreted as including rather than exclusive or exhaustive; that is, meaning "including but not limited to."

[0041] The following detailed description of the correction method of this disclosure is provided to further illustrate the feasibility of the inventive concept of this disclosure, the advanced nature of the inventive effects that can be produced, and the rationality of the technical solution, thereby helping to understand the method of this disclosure.

[0042] The multi-well elastic parameter consistency correction method disclosed herein, which considers the influence of burial depth compaction, combines depth trend analysis with histogram correction to make the correction results more consistent with regional geological patterns. The technical solution is as follows:

[0043] By conducting background research on the structural region, standard layers and reference wells within the correction area are identified. By statistically analyzing and trend-fitting the sonic, density, resistivity, and natural gamma curves of the reference wells within the standard layer section, regional correlation is obtained. The differences generated by the regional correlation are then corrected using histograms. The corrected differences are then backfilled to complete the consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction.

[0044] To facilitate those skilled in the art in better understanding the implementation steps of the present invention, the present invention will be described in detail below with reference to the accompanying drawings, such as... Figure 4 As shown in the embodiments of this disclosure, the method for consistent correction of elastic parameters of multiple wells considering the influence of burial depth and compaction includes the following steps:

[0045] Step S10: Determine the standard layers and reference wells within the calibration area, as follows:

[0046] (1) Select trend analysis wells within the calibration area, and set the standard layer and curve category for trend analysis. The selection method is to use wells whose sonic, density, resistivity, natural gamma curves cover the target layer in the study area as the trend analysis wells.

[0047] (2) Perform statistical analysis on the logging curves of the selected trend analysis wells to determine whether the logging response characteristics of the target layer are abnormal. If there are abnormalities, it is necessary to combine the formation sedimentary characteristics to decide whether to remove the abnormal values ​​or remove the well.

[0048] (3) After the statistical analysis is completed, reference wells are selected according to the standard layer. The reference wells are the regional standard well data obtained by taking the arithmetic mean of all the wells selected in step (2). Then, the depth trend analysis is completed using the standard well data and applied to the entire work area.

[0049] In this embodiment of the disclosure, a seismic rock physics analysis application system (hereinafter referred to as RPS software) is used to select reference wells and standard layers. The specific operation page is as follows: Figure 1 As shown.

[0050] Step S20: Perform depth trend analysis on the reference well curve data within the standard layer to obtain regional correlation, as detailed below:

[0051] In this embodiment of the disclosure, the standard layers involved in the scheme are mainly provided by geologists, and the regional correlation requires data such as sonic waves, density, resistivity, and natural gamma curves, which can be obtained through well logging technology.

[0052] In this embodiment of the disclosure, depth trend analysis is performed on the reference well curve data in the standard section. This mainly involves projecting the trend analysis data into a scatter plot and selecting an algorithm for trend fitting.

[0053] The most commonly used fitting algorithm is a bivariate k-th degree polynomial, and the equation can be simply expressed as:

[0054] A0 = c1 + c2x + c3y + c4x 2 +c5xy+c6y 2 +…;

[0055] In the formula: A0 represents the logging response trend value; c i (i = 1, 2, 3, ...) represents non-fixed coefficients; (x, y) represents the horizontal and vertical coordinates of a certain well location.

[0056] There will be random errors between the fitted well logging response trend value and the actual surface, i.e.:

[0057] e = A - A0;

[0058] In the formula: A represents the true value, A0 represents the fitted trend value, and e represents the random error.

[0059] The fitting principle is to make the fitted trend value as close as possible to the true value, which means making the random error e approach 0.

[0060] In this embodiment of the disclosure, depth trend analysis is performed on reference well curve data using RPS software in a standard section to obtain the regional fitting trend relationship. The specific operation page is as follows: Figure 2 As shown.

[0061] Step S30: Perform histogram correction processing and correction amount backfilling on the regional correlation relationship to obtain the depth trend correction result, as follows:

[0062] In the obtained regional fitting trend relationship, the trend difference is projected using a histogram, and the regional difference is corrected by histogram. After the histogram-corrected regional difference is processed for consistency, it must be corrected by regional data before the correction amount can be filled back, and then the final depth trend correction result can be obtained.

[0063] Step S40: Verify the calibration results. The specific verification method is as follows:

[0064] The construction depth trend surface is obtained through the plane interpolation module of RPS software. Figure 3-1 ) and the trend surface of the depth trend correction result ( Figure 3-2 If the structural trend is consistent with the correction result and there is no "bull's eye" phenomenon, it indicates that the correction effect is good and the corrected curve can be applied to seismic inversion reservoir prediction. If the two trends are inconsistent, it indicates that there is a problem with the correction result. It may be that there is a problem with the selection of parameters or standard layers, or there may be a problem with the provided well logging curve data. If all of the above problems can be ruled out, it means that the depth trend correction method is not applicable to this area.

[0065] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for consistency correction of elastic parameters in multiple wells considering the influence of burial depth and compaction, characterized in that, include: Identify the standard layers and reference wells within the calibration area; Depth trend analysis was performed on the reference well curve data within the standard layer to obtain regional correlation. The differences generated by the regional correlation are corrected by histogram, and the corrected differences are backfilled to complete the consistency correction of the elastic parameters of multiple wells considering the influence of burial depth and compaction.

2. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction as described in claim 1, characterized in that, The method for determining the standard layer and reference well within the correction area includes: Within the calibration area, select trend analysis wells and set the standard layers and curve categories for trend analysis. The trend analysis wells include wells that cover the target layer with sonic, density, resistivity, and natural gamma curves. After removing anomalies from the trend analysis wells and their logging curves, reference wells are selected according to standard layers. The reference wells are regional standard wells obtained by taking the arithmetic mean of all trend analysis wells after the anomaly removal process.

3. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction as described in claim 2, characterized in that, The method for removing anomalies from the trend analysis well and its logging curves includes: Determine whether the logging response characteristics of the target layer are abnormal. If abnormal, decide whether to remove the abnormal value or remove the well based on the formation sedimentary characteristics.

4. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction as described in claim 2, characterized in that, The method for performing depth trend analysis on reference well curve data within the standard layer to obtain regional correlation includes: The data for in-depth trend analysis is projected and analyzed in scatter form, and the algorithm for trend fitting is selected. The fitting algorithm is a bivariate k-th degree polynomial, and the equation is expressed as follows: A0=c1+c2x+c3y+c4x 2 +c5xy+c6y 2 +…; In the formula: A0 represents the logging response trend value; c i (i = 1, 2, 3, ...) represents non-fixed coefficients; (x, y) represents the horizontal and vertical coordinates of a certain well location; The random error between the fitted logging response trend value and the actual surface is expressed as: e = A - A0; In the formula: A represents the true value, A0 represents the fitted trend value, and e represents the random error; The fitting principle is to make the fitted trend value infinitely close to the true value, that is, to make the random error e infinitely close to 0.

5. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction as described in claim 2, characterized in that: Determining the correlation of the region requires obtaining acoustic, density, resistivity, and natural gamma curve data through well logging techniques.

6. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth compaction according to any one of claims 1-5, characterized in that, The method for performing histogram correction on the differences generated by the regional correlation, and then backfilling the corrected differences to complete the consistency correction of multi-well elastic parameters considering the influence of burial depth and compaction, includes: In the aforementioned regional correlation, a histogram is used to project the trend difference, and the regional difference is simultaneously corrected using a histogram. After the histogram-corrected regional difference undergoes consistency processing, the correction amount is backfilled after regional data correction to obtain the deep trend correction result.

7. The method for consistency correction of elastic parameters of multiple wells considering the influence of burial depth and compaction as described in claim 6, characterized in that, The correction method further includes: The verification method involves comparing the constructed depth trend surface with the depth trend correction result trend surface. If the constructed trend and the correction result trend are consistent and there is no bullseye phenomenon, it indicates that the correction effect is good. If the two trends are inconsistent, it indicates that there is a problem with the correction result. If the problems with parameters, standard layer selection and logging curve data are excluded, it indicates that the above correction method is not applicable to the corresponding area.

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