Well logging curve standardization method and device, electronic equipment and storage medium

Abstract

The invention provides a logging curve standardization method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a quantitative index used for evaluating the features of a marker bed corresponding to a target well, and dividing a stratum boundary corresponding to each marker bed; for each marker layer, configuring a corresponding index weight for the quantitative index corresponding to the marker layer, and determining a recommendation coefficient corresponding to the marker layer; screening a target mark layer with the highest recommendation coefficient; according to the well feature data and a preset standard well screening rule, screening a standard well from the target wells; in the target wells, a correction well which is different from the standard well in logging curve value is screened, and the curve correction value corresponding to the correction well is determined with the logging curve value corresponding to the target marker bed of the standard well as the benchmark; and processing the target logging curve according to the curve correction value. The accuracy and rationality of selection of the standard well and the marker bed can be improved, and meanwhile the generation accuracy of the correction value in the standardization processing process of the logging curve is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of well logging data processing, and in particular to a well logging curve standardization method, device, electronic equipment and storage medium. Background Art

[0002] In the existing technical solutions, the commonly used methods for logging curve standardization are histogram analysis and trend surface analysis. Among them, the histogram analysis method uses the logging data (such as neutron, density, acoustic wave time difference, etc.) of the key well marker layer after environmental impact correction to make histograms and frequency cross-plots as the calibration mode for logging data standardization. By analyzing the frequency distribution of the logging data of the standard layer of each well, the characteristic values ​​of the marker layer of each well are calculated and obtained, and the characteristic values ​​of the marker layer of the key well are compared one by one to check the reliability of each logging data and determine the correction amount; the trend surface analysis method assumes that the logging response value reflecting the regional change characteristics of the formation will appear as a natural trend in space, so it can be depicted as a digital surface, called a trend surface. The trend surface analysis method can be used to make the best fit of the spatial distribution of the real logging response value of a certain standard layer based on the data of a certain well point, and when the logging response value of the measured standard layer deviates from the trend value, the difference can be calculated to correct it.

[0003] However, both the histogram analysis method and the trend surface analysis method have certain limitations. Specifically, when using the histogram to standardize the curve, the characteristic value of the standard layer will be corrected to the same value. If the real trend exists, it will be excluded in the standardization process, resulting in the curve not being able to correctly reflect the planar sedimentary characteristics of the formation, and the formation heterogeneity will be ignored, which is unreasonable; when using the trend surface to standardize the curve, if there are local abnormal points affected by structure or sedimentation, the curve value of the abnormal point participates in the trend surface fitting, which will cause the standard value of the standard layer of the local well to be larger or smaller as a whole, and the trend surface method cannot effectively standardize the logging curve. Summary of the invention

[0004] The embodiments of the present disclosure at least provide a method, device, electronic device and storage medium for well logging curve standardization, which can improve the accuracy and rationality of selecting standard wells and marker layers, and at the same time improve the accuracy of generating correction values ​​in the process of standardizing well logging curves.

[0005] The present disclosure provides a method for normalizing a well logging curve, including:

[0006] Obtaining a target logging curve, determining a quantitative index for evaluating the characteristics of a marker layer corresponding to the target well according to the target logging curve, and dividing the stratigraphic boundary corresponding to each marker layer;

[0007] For each of the marker layers, a corresponding indicator weight is configured for the quantitative indicator corresponding to the marker layer, and a recommendation coefficient corresponding to the marker layer is determined according to the indicator weight; and a target marker layer having the highest recommendation coefficient is selected;

[0008] Determine the well characteristic data corresponding to all the target wells within the preset block range; select standard wells from the target wells according to the well characteristic data and preset standard well screening rules;

[0009] Among the target wells, a correction well having a difference in well logging curve value from the standard well is selected, and the curve correction amount corresponding to the correction well is determined based on the well logging curve value corresponding to the target marker layer of the standard well;

[0010] The target logging curve is processed according to the curve correction amount.

[0011] In an optional implementation manner, determining, based on the target well logging curve, a quantitative index for evaluating the characteristics of the marker layer corresponding to the target well specifically includes:

[0012] The marker layer characteristics include electrical characteristics, lateral distribution characteristics and lithological characteristics;

[0013] With respect to the electrical characteristics, determining the mean similarity and variance similarity between the target logging curve and the logging curve of a preset reference well as the quantitative index;

[0014] According to the lateral distribution characteristics, the curve similarity between the target logging curve and the logging curve of the preset reference well is evaluated by dynamic time warping as the quantitative index;

[0015] According to the lithological characteristics, the curve smoothness corresponding to the target logging curve is determined as the quantitative index.

[0016] In an optional implementation manner, for each of the marker layers, configuring a corresponding indicator weight for the quantitative indicator corresponding to the marker layer, and determining a recommendation coefficient corresponding to the marker layer according to the indicator weight; and selecting a target marker layer with the highest recommendation coefficient specifically includes:

[0017] Constructing an evaluation matrix of the marker layer in terms of the electrical characteristics, the lateral distribution characteristics and the lithological characteristics indicators;

[0018] For each element in the evaluation matrix, a corresponding indicator score value is configured for the element;

[0019] According to the quantitative indicator and the indicator score value, determine the indicator weight corresponding to the quantitative indicator by using the sum-product method or the square root method;

[0020] Performing normalized summation on the indicator weight and the corresponding quantitative indicator to determine the recommendation coefficient;

[0021] For each target well, the marker layers are sorted from high to low according to the recommendation coefficients, and the marker layer with the highest recommendation coefficient is determined as the target marker layer corresponding to the target well.

[0022] In an optional implementation, the marker layers of all wells within the preset block range are determined based on the following steps:

[0023] According to the structural type corresponding to the target well, a corresponding minimum distance between wells is set;

[0024] For the wells within the minimum well-to-well distance range, the equal thickness comparison principle is adopted to identify the top and bottom boundary depths of the marker layer corresponding to the comparison well according to the thickness of the marker layer corresponding to the marker layer of the target well;

[0025] For wells outside the minimum well-to-well distance range, determine the candidate depth area of ​​the comparison well marker layer according to the preset top and bottom boundary depth error range;

[0026] Determine, according to the curve similarity between the well logging curve corresponding to the selected depth area of ​​the standby comparison well and the target well logging curve of the target well, the curve similarity segment between the top and bottom boundary curves of the target marker layer in the well logging curve corresponding to the depth area of ​​the comparison well and the target well logging curve of the target well;

[0027] In the curve similarity section, the depth with the same curve value as the top and bottom boundary curve of the target well is selected as the top and bottom boundary depth of the corresponding marker layer of the comparison well.

[0028] In an optional implementation manner, the curve correction amount corresponding to the correction well is determined based on the well logging value corresponding to the target marker layer of the standard well, specifically including:

[0029] For the target marker layer corresponding to each target well, dividing the logging curve value into a plurality of target segments;

[0030] Counting the frequency of the logging curve value falling into each target segment, and determining the logging value frequency distribution histogram corresponding to each target well;

[0031] Determine the difference between the logging curve values ​​corresponding to the maximum frequency in the logging value frequency distribution histogram of the standard well and the calibration well;

[0032] The difference is determined as the correction amount.

[0033] In an optional implementation manner, after determining the curve correction amount corresponding to the correction well based on the well logging value corresponding to the target marker layer of the standard well, the method further includes:

[0034] determining whether the difference between the standard well and the calibration well is caused by a logging series;

[0035] If so, the correction is applied to all wells in the logging series;

[0036] If not, the correction amount corresponding to each well is applied to each well respectively.

[0037] In an optional implementation manner, after processing the target logging curve according to the curve correction amount, the method further includes:

[0038] Draw a trend surface diagram corresponding to the correction amount, a relative error trend surface diagram, and a trend surface diagram corresponding to the corrected logging curve value.

[0039] The present disclosure also provides a well logging curve standardization device, including:

[0040] A marker layer division module is used to obtain a target well logging curve, determine a quantitative index for evaluating the marker layer characteristics corresponding to the target well according to the target well logging curve, and divide the formation boundary corresponding to each marker layer;

[0041] The preferred marker layer determination module is used to configure a corresponding indicator weight for the quantitative indicator corresponding to each marker layer, and determine a recommendation coefficient corresponding to the marker layer according to the indicator weight; and select a target marker layer with the highest recommendation coefficient;

[0042] A standard well screening module is used to determine well characteristic data corresponding to all the target wells within a preset block range; and screen standard wells from the target wells according to the well characteristic data and preset standard well screening rules;

[0043] A correction amount determination module is used to select, from the target wells, correction wells that have differences in well logging curve values ​​from the standard wells, and determine the curve correction amount corresponding to the correction wells based on the well logging curve value corresponding to the target marker layer of the standard wells;

[0044] The standardization processing module is used to process the target logging curve according to the curve correction amount.

[0045] An embodiment of the present disclosure also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the above-mentioned logging curve standardization method or steps in any possible implementation of the above-mentioned logging curve standardization method are executed.

[0046] The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned well logging curve standardization method or the steps in any possible implementation of the above-mentioned well logging curve standardization method are executed.

[0047] The embodiment of the present disclosure also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the above-mentioned well logging curve standardization method, or the steps in any possible implementation of the above-mentioned well logging curve standardization method.

[0048] The embodiments of the present disclosure provide a method, device, electronic device and storage medium for standardizing a well logging curve. The method obtains a target well logging curve, determines a quantitative index for evaluating the characteristics of a marker layer corresponding to a target well according to the target well logging curve, and divides the formation boundary corresponding to each marker layer; configures a corresponding index weight for the quantitative index corresponding to each marker layer for each marker layer, and determines a recommended coefficient corresponding to the marker layer according to the index weight; selects a target marker layer with the highest recommended coefficient; determines well characteristic data corresponding to all target wells within a preset block range; selects standard wells from the target wells according to the well characteristic data and preset standard well screening rules; selects correction wells from the target wells that have differences in well logging curve values ​​from the standard wells, and determines the curve correction amount corresponding to the correction wells based on the well logging curve value corresponding to the target marker layer of the standard well; and processes the target well logging curve according to the curve correction amount. The accuracy and rationality of selecting standard wells and marker layers can be improved, and the accuracy of generating correction amounts in the process of standardizing well logging curves can be improved.

[0049] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following is a brief introduction to the drawings required for use in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can also be obtained based on these drawings without creative work.

[0051] Figure 1 A flow chart of a well logging curve standardization method provided by an embodiment of the present disclosure is shown;

[0052] Figure 2 A flow chart of a method for determining a marker layer provided by an embodiment of the present disclosure is shown;

[0053] Figure 3 A schematic diagram of a well logging curve standardization device provided by an embodiment of the present disclosure is shown;

[0054] Figure 4 A schematic diagram of an electronic device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0056] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0057] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0058] After research, it was found that in the existing technical solutions, both the histogram analysis method and the trend surface analysis method have certain limitations. Specifically, when using the histogram to standardize the curve, the characteristic value of the standard layer will be corrected to the same value. If the real trend exists, it will be excluded in the standardization process, resulting in the curve not being able to correctly reflect the planar sedimentary characteristics of the formation, and the formation heterogeneity will be ignored, which is unreasonable; when using the trend surface to standardize the curve, if there are local abnormal points affected by structure or sedimentation, the curve value of the abnormal point participates in the trend surface fitting, which will cause the standard value of the standard layer of the local well to be larger or smaller as a whole, and the trend surface method cannot be used to effectively standardize the logging curve.

[0059] Based on the above research, the present disclosure provides a method, device, electronic device and storage medium for standardizing a well logging curve, which obtains a target well logging curve, determines a quantitative index for evaluating the characteristics of a marker layer corresponding to a target well according to the target well logging curve, and divides the formation boundary corresponding to each marker layer; for each marker layer, configures a corresponding index weight for the quantitative index corresponding to the marker layer, and determines the recommended coefficient corresponding to the marker layer according to the index weight; selects the target marker layer with the highest recommended coefficient; determines the well characteristic data corresponding to all the target wells within a preset block range; selects standard wells in the target wells according to the well characteristic data and preset standard well screening rules; selects correction wells that have differences in well logging curve values ​​from the standard wells in the target wells, and determines the curve correction amount corresponding to the correction wells based on the well logging curve value corresponding to the target marker layer of the standard well; and processes the target well logging curve according to the curve correction amount. The accuracy and rationality of selecting standard wells and marker layers can be improved, and the accuracy of generating correction amounts in the process of standardizing well logging curves can be improved.

[0060] To facilitate understanding of this embodiment, a logging curve standardization method disclosed in the embodiment of the present disclosure is first introduced in detail. The execution subject of the logging curve standardization method provided in the embodiment of the present disclosure is generally a computer device with certain computing capabilities, and the computer device includes, for example: a terminal device or a server or other processing device, and the terminal device can be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the logging curve standardization method can be implemented by a processor calling a computer-readable instruction stored in a memory.

[0061] See also Figure 1 FIG. 1 is a flow chart of a method for normalizing a well logging curve provided by an embodiment of the present disclosure, wherein the method comprises steps S101 to S105, wherein:

[0062] S101, obtaining a target logging curve, determining a quantitative index for evaluating characteristics of a marker layer corresponding to the target well according to the target logging curve, and dividing a formation boundary corresponding to each marker layer.

[0063] In the specific implementation, the various indicators for evaluating the characteristics of the marker layers are first quantified and calculated, and then the stratigraphic boundaries of the marker layers are determined using the window monitoring method.

[0064] Specifically, the marker layer characteristics include electrical characteristics, lateral distribution characteristics and lithological characteristics; for the electrical characteristics, the mean similarity and variance similarity between the target logging curve and the logging curve of the preset reference well are determined as quantitative indicators; for the lateral distribution characteristics, the curve similarity between the target logging curve and the logging curve of the preset reference well is evaluated through dynamic time warping as a quantitative indicator; for the lithological characteristics, the curve smoothness corresponding to the target logging curve is determined as a quantitative indicator.

[0065] Here, one of the signs of the marker layer is that the electrical characteristics are obvious and the curves are highly comparable. Therefore, the mean similarity and variance similarity are used to evaluate the logging curves.

[0066] Among them, a well with reliable and complete data in the block is selected as the preset reference well, and the depth corresponding to each formation of the known well is obtained according to the formation data, and one or more logging curves are selected, and the curve value corresponding to each depth value on the selected logging curve after preprocessing is obtained according to the depth corresponding to the formation. According to the curve value corresponding to the depth point on the selected logging curve, the mean similarity of the same logging curves of the corresponding formations of each two known wells is obtained (the corresponding formations refer to two formations with the same name, and the same logging curve refers to the first logging curve with the same name).

[0067] After that, in addition to the mean similarity, the variance similarity can also be selected to evaluate the characteristics of the marker layer curve. The method for calculating the variance similarity is consistent with the method for calculating the mean similarity. The variance of the curve values ​​of all observation points in the first corresponding window pane on the corresponding first logging curve is calculated, and the variance is defined as the first variance; similarly, the variance of the curve values ​​of all observation points in the second corresponding window pane on the corresponding first logging curve is calculated, and the variance is defined as the second variance; the variance similarity of the same logging curves in the corresponding windows of two known wells is the difference between the first variance and the second variance. The smaller the value of the variance similarity, the higher the similarity of the corresponding formations of the two known wells, and it is believed that the fluctuation degree of the logging curve segments of the corresponding formations of the two known wells tends to be the same. It is worth noting that the calculation of the mean similarity and the variance similarity should be compared and calculated layer by layer and well by well according to the stratum.

[0068] Furthermore, one of the signs of selecting a marker layer is to select a layer with stable lateral distribution. Through the isochronous characteristics of the marker layer, the curve similarity is evaluated using the curve dynamic time warping method to characterize the lateral distribution stability of the marker layer.

[0069] Here, dynamic time warping calculates the similarity between two time series by extending and shortening the time series, and uses the dynamic time warping algorithm to obtain the morphological similarity of the same logging curves of each two known wells corresponding to the formation. The distance between the observation points of the two known wells corresponding to the formation is calculated to obtain the observation point distance matrix.

[0070] Among them, the distance of each possible path is calculated in the observation point distance matrix. It should be noted that the selected path must start from the lower left corner square of the observation point distance matrix and end at the upper right corner square, and each square cannot be passed repeatedly. According to the shortest path, the morphological similarity of the same logging curves of the corresponding formations of two known wells is obtained.

[0071] Furthermore, one of the markers of the selected marker layer is a layer of single lithology, which can be represented on the logging curve by the smoothness of the curve.

[0072] Here, a logging curve in the well is selected to calculate the smoothness of the logging curve based on the sampling point data. The smoothness of the curve is used to characterize its single lithology and single composition. Using the selected logging curve, the smoothness of the logging curve is calculated according to the width of each window pane, which can be expressed by the overall volatility of the curve value on the curve and the size and number of the curve sawtooth.

[0073] As a possible implementation method, the combination of the variance and variation of the curve value of each pane is defined as the smoothness of the well logging curve of the required processing section. Specifically, the following steps may be included:

[0074] Step 1: Calculate the variance of the selected logging curve.

[0075] In a specific implementation, the variance can reflect the size of the overall volatility of the data. Therefore, the variance of the logging curve value in the pane is used to represent its overall volatility.

[0076] Step 2: Calculate the variation of the logging curve value selected in the window pane.

[0077] In specific implementation, the larger and more sawtooth in the logging curve, the greater the volatility of the curve; on the contrary, the smaller and fewer sawtooth, the smaller the volatility of the curve. The variogram can better reflect the size of the local volatility of the data.

[0078] Step 3: Calculate the smoothness of the selected curve.

[0079] The variance reflects the overall volatility of the data, and the variation reflects the local volatility of the data. The square root of the sum of the two is defined as the variation variance root, which is used to comprehensively reflect the smoothness of the curve in the processing layer section.

[0080] Furthermore, the sliding window detection method is used to determine the stratigraphic boundaries of each target well. The first marker stratigraphic layer and the last marker stratigraphic layer of the target well are first divided, and then the remaining marker stratigraphic layers are divided, and the remaining marker stratigraphic layers are used as the marker stratigraphic layers of the intermediate area. According to the first candidate area of ​​the target well, the last candidate area of ​​the target well, and the selected logging curve, the sliding window monitoring method is used to determine the stratigraphic boundary values ​​of the first marker stratigraphic layer and the last marker stratigraphic layer of the target well.

[0081] Specifically, the first sliding area of ​​the target well is determined according to the upper and lower boundary values ​​of the first candidate area and the upper and lower boundary values ​​of the last candidate area; the first area is acquired in real time by sliding the sliding window in the first sliding area, and the first curve segment corresponding to the first area on the first curve is acquired; the second curve segment corresponding to the comparison well marker layer corresponding to the first candidate area and the last candidate area on the second curve is acquired respectively, and the first curve similarity between the first curve segment and the corresponding second curve segment is acquired; the optimal first area is determined according to the first curve similarity, and the stratigraphic boundary values ​​of the first marker formation and the last marker formation are acquired according to the optimal first area, and so on, to divide the boundary value of each marker layer.

[0082] S102: For each marker layer, configure a corresponding indicator weight for the quantitative indicator corresponding to the marker layer, and determine a recommendation coefficient corresponding to the marker layer according to the indicator weight; and select a target marker layer with the highest recommendation coefficient.

[0083] In the specific implementation, an evaluation matrix of the marker layer in terms of electrical characteristics, lateral distribution characteristics and lithological characteristics is constructed; for each element in the evaluation matrix, a corresponding indicator score value is configured for the element; based on the quantitative indicators and the indicator score values, the indicator weights corresponding to the quantitative indicators are determined by the sum-product method or the square root method; the indicator weights and the corresponding quantitative indicators are normalized and summed to determine the recommendation coefficients; for each target well, the marker layers are sorted from high to low according to the recommendation coefficients, and the marker layer with the highest recommendation coefficient is determined as the target marker layer corresponding to the target well.

[0084] Here, the analytic hierarchy process is used to intelligently identify the marker layer based on the weight importance score of the business expert indicators. The analytic hierarchy process refers to treating a complex multi-objective decision-making problem as a system, decomposing the target into multiple targets (such as lithology, thickness, electrical properties, physical properties, oil and gas content, etc.) or criteria (such as stable distribution, thick thickness, single lithology, and non-permeable reservoirs with reliable four-property relationships as marker layers), and then decomposing them into several levels of multiple indicators (or criteria, constraints), and calculating the hierarchical single ranking (weight) and total ranking through the fuzzy quantification method of qualitative indicators as a systematic method for optimizing decision-making with targets (multiple indicators) and multiple schemes.

[0085] Among them, based on the hierarchical analysis method, on the basis of expert scoring, the calculated curve similarity, curve smoothness and other indicators are used, and the sum-product method or square root method is used to determine the weight of each indicator, and the recommended coefficient of each marker layer of each well is calculated, and the layer with the highest recommended coefficient is selected as the marker layer of the block.

[0086] S103, determining well characteristic data corresponding to all the target wells within a preset block range; and selecting standard wells from the target wells according to the well characteristic data and preset standard well screening rules.

[0087] In specific implementation, the principle for selecting standard wells is that the wells with good logging data quality, high logging series accuracy and good well conditions in the block are selected as standard wells. Generally, exploratory wells in the block are selected as standard wells. In this embodiment, the software system is used to automatically obtain the well characteristic data of all wells in the block, including well type, well type, logging series and corresponding curve accuracy, and judge the well condition (mainly whether there is diameter expansion or wellbore collapse) through the well diameter curve and the maximum, minimum and median values ​​of the wellbore diameter.

[0088] Here, it is preferred to select wells that are exploration and evaluation wells. Secondly, the logging series are queried within the selected well range. If there are wells with different logging series, the curve accuracy of different logging series is queried to select the wells corresponding to the logging series with high curve accuracy. Finally, the well diameter curve and wellbore diameter and other data are queried within the selected well range. The minimum, maximum and mean values ​​of the difference between the well diameter and the wellbore diameter are used to determine whether the diameter expansion has occurred. The system sets a threshold. If the calculation result exceeds the set threshold, it is considered that the well has expanded and the well is eliminated. Similarly, wells that do not meet the standard well requirements are eliminated step by step, and finally wells that meet the requirements are automatically pushed out as standard wells. The push result may be one well or multiple wells.

[0089] S104, selecting, from the target wells, correction wells having different well logging curve values ​​from the standard wells, and determining the curve correction amount corresponding to the correction wells based on the well logging curve value corresponding to the target marker layer of the standard wells.

[0090] In the specific implementation, the differences between the standard well marker layer and the calibration well marker layer in terms of logging series, instrument calibration, drilling fluid performance, etc. The software provides single well mapping tools and histogram analysis tools to automatically perform analysis and comparison, visualize the wells with differences and input them as calibration wells to the next step.

[0091] Here, for the target marker layer corresponding to each target well, the logging curve value is divided into multiple target segments; the frequency of the logging curve value falling into each target segment is counted to determine the logging value frequency distribution histogram corresponding to each target well; the difference between the logging curve value corresponding to the maximum frequency in the logging value frequency distribution histogram of the standard well and the correction well is determined; and the difference is determined as the correction amount.

[0092] Specifically, the characteristic values ​​of wells in different logging series are calculated using statistical histograms, and the logging values ​​of marker layers of different wells are divided into several sections. The frequency of the logging values ​​of the marker layers of each well falling into each section is counted, and the frequency histogram of each well is drawn accordingly, and compared with the characteristic values ​​of the marker layers of the standard wells. According to the principle that the peak value of the marker layer frequency histogram or its frequency distribution should remain basically unchanged, the characteristic value of the marker layer of the standard well is used as the judgment standard, and the curve values ​​of all wells are corrected to a unified scale range through calculation and analysis.

[0093] Here, assuming that the logging values ​​of the marker layer are divided into n segments, the probability statistics of the logging values ​​of each segment are performed separately, which conforms to the probability distribution function of discrete random variables and satisfies:

[0094]

[0095] Wherein, P(i)=max(p(xi)), x is the logging curve value in this interval. The correction value can be obtained by subtracting the maximum frequency characteristic value corresponding to the calibration well marker layer from the characteristic value corresponding to the maximum frequency of the standard well marker layer.

[0096] In this way, after the correction processing, the correction amount, relative error, corrected eigenvalue and other data can be obtained. The probability histogram tool and probability curve graph tool provided by the software can be used to display the well data before and after correction, which is convenient for researchers to analyze and compare.

[0097] As a possible implementation, after step S104, it can also be determined whether the difference between the standard well and the correction well is caused by the logging series; if so, the correction amount is applied to all wells under the logging series; if not, the correction amount corresponding to the well is applied to each well respectively.

[0098] Here, for wells whose differences are caused by the logging series, the correction amount of each well is used to calculate the correction amount of the logging series through the probability statistical histogram, and the correction amount is applied to all wells under the logging series; for wells whose differences are not caused by the logging series, the correction amount is applied to each well separately.

[0099] S105: Process the target logging curve according to the curve correction amount.

[0100] In the specific implementation, the contour map analysis tool provided by the software can be used to draw trend maps such as the correction amount trend map, the relative error trend map and the corrected eigenvalue trend map, and analyze the rationality of the correction through the trend map. If there are singular points in the trend map, it is necessary to remove the abnormal values ​​and refresh the trend map, and repeat this process until a satisfactory trend map is obtained and the correction amount is statistically calculated to complete the curve standardization.

[0101] Here, since the response characteristics of the standard layer have certain changes in the horizontal direction, a trend surface equation that roughly conforms to a certain trend can be fitted. With the well location coordinates as x, y, and z representing the measured value at the data point (x, y) in the area on a plane, the corresponding value of each well in the working area on the trend surface is the trend value of the well. The commonly used quadratic polynomial equation is as follows:

[0102] z′=b1+b2x+b3y+b4x2+b5xy+b6y2+...

[0103] Among them, z' represents the logging trend value of a certain point, x and y are the well coordinates, bi is the undetermined coefficient of the polynomial (i = 1, 2, 3...), and the correction value can be obtained by using z'-z.

[0104] The embodiment of the present disclosure provides a method for normalizing a well logging curve, which obtains a target well logging curve, determines a quantitative index for evaluating the characteristics of a marker layer corresponding to a target well according to the target well logging curve, and divides the formation boundary corresponding to each marker layer; for each marker layer, configures a corresponding index weight for the quantitative index corresponding to the marker layer, and determines the recommended coefficient corresponding to the marker layer according to the index weight; selects a target marker layer with the highest recommended coefficient; determines the well characteristic data corresponding to all the target wells within a preset block range; selects a standard well in the target well according to the well characteristic data and a preset standard well screening rule; selects a correction well that has a difference in the well logging curve value from the standard well in the target well, and determines the curve correction amount corresponding to the correction well based on the well logging curve value corresponding to the target marker layer of the standard well; and processes the target well logging curve according to the curve correction amount. The accuracy and rationality of selecting standard wells and marker layers can be improved, and the accuracy of generating the correction amount in the process of normalizing the well logging curve can be improved.

[0105] See also Figure 2 FIG. 2 is a flowchart of a method for determining a marker layer provided by an embodiment of the present disclosure, wherein the method comprises steps S201 to S205, wherein:

[0106] Step S201: according to the structural type to which the target well corresponds, set the corresponding minimum distance between wells.

[0107] Step S202: for the wells within the minimum well-to-well distance range, the equal thickness comparison principle is adopted to identify the top and bottom boundary depths of the marker layer corresponding to the well according to the thickness of the marker layer corresponding to the target marker layer.

[0108] Step S203: for the wells outside the minimum well-to-well distance range, determine the candidate depth region of the marker layer of the well according to the preset top and bottom boundary depth error range.

[0109] Step S204: Determine the curve similarity segments between the top and bottom boundary curves of the target marker layer in the well logging curve corresponding to the depth area and the target well logging curve according to the curve similarity between the well logging curve corresponding to the candidate depth area and the target well logging curve.

[0110] Step S205: In the curve similarity segment, select the depth with the same curve value as the top and bottom boundary curve as the top and bottom boundary depth of the corresponding marker layer of the well.

[0111] In specific implementation, since the strata are affected by the structure and sedimentary environment during the deposition process, there may be certain changes in the lateral distribution of the strata, and the changes are manifested as changes in the depth of the top and bottom interfaces and changes in the sedimentary thickness. On the basis of the equal thickness comparison method, the relative error of the top and bottom boundaries of the marker layer is set according to the distance between wells, and the range of the top and bottom boundaries of the marker layer to be determined is formed according to the distance between wells. The aforementioned curve similarity comparison method is used to compare the morphological characteristics of the top and bottom interface curves of the selected marker layer within the top and bottom boundaries, and finally the top and bottom boundary depths of the marker layer of the comparison well are determined.

[0112] Here, for a certain block, the user sets the minimum distance between wells for identifying marker layers according to the structural type to which it belongs. For example, if a block is a monocline structure, the minimum distance between wells for identification is set to 5 km, and the relative error for identifying marker layers between wells is set to 10%. This means that within the minimum distance between wells, it can be considered that the strata are basically not affected by the structure and sedimentary environment, and the thickness of the marker layers should be the same. The top and bottom boundary depths of the marker layers of the wells within this range can be directly identified using the equal thickness comparison principle. For wells whose distance between wells exceeds the minimum distance between wells, the relative error for identification is set to 10%. For example, wells identified by equal thickness comparison 1 The bottom boundary depth of the marker layer is h1, and the thickness of the marker layer of the selected well is H, then the depth range of the candidate area of ​​Well 1 is h1-0.1*H~h1+0.1*H; for example, the bottom boundary of the marker layer obtained by Well 2 and Well 1 according to the principle of equal thickness is h2, and the well spacing between Well 2 and Well 1 exceeds the minimum well spacing, then the range of the candidate area of ​​the bottom boundary of the marker layer of Well 2 obtained by comparing with Well 1 is h2-0.1×(H+0.1H)~h2+0.1×(H+0.1H), and so on. According to the set minimum well distance and relative error for marker layer identification, the range of the candidate area of ​​the marker layer of all wells in the block can be obtained.

[0113] In this way, based on the determined candidate marker layer area, the curve similarity comparison is used to identify the similar segments between the candidate area curve and the top and bottom boundary curves of the selected well marker layer, and the depth with the same value as the bottom boundary curve of the selected well marker layer is selected in the comparison curve as the bottom boundary depth of the comparison well marker layer. This approach saves a lot of manual division and adjustment of the marker layer, and uses computer automatic processing to automatically identify the marker layers of all wells in the entire area, which can greatly improve work efficiency.

[0114] The embodiment of the present disclosure provides a method for normalizing a well logging curve, which obtains a target well logging curve, determines a quantitative index for evaluating the characteristics of a marker layer corresponding to a target well according to the target well logging curve, and divides the formation boundary corresponding to each marker layer; for each marker layer, configures a corresponding index weight for the quantitative index corresponding to the marker layer, and determines the recommended coefficient corresponding to the marker layer according to the index weight; selects a target marker layer with the highest recommended coefficient; determines the well characteristic data corresponding to all the target wells within a preset block range; selects a standard well in the target well according to the well characteristic data and a preset standard well screening rule; selects a correction well that has a difference in the well logging curve value from the standard well in the target well, and determines the curve correction amount corresponding to the correction well based on the well logging curve value corresponding to the target marker layer of the standard well; and processes the target well logging curve according to the curve correction amount. The accuracy and rationality of selecting standard wells and marker layers can be improved, and the accuracy of generating the correction amount in the process of normalizing the well logging curve can be improved.

[0115] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0116] Based on the same inventive concept, the embodiment of the present disclosure also provides a well logging curve standardization device corresponding to the well logging curve standardization method. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the above-mentioned well logging curve standardization method in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0117] See also Figure 3 , Figure 3 A schematic diagram of a logging curve standardization device provided in an embodiment of the present disclosure. Figure 3 As shown in , the well logging curve standardization device 300 provided in the embodiment of the present disclosure includes:

[0118] The marker layer division module 310 is used to obtain a target well logging curve, determine a quantitative index for evaluating the marker layer characteristics corresponding to the target well according to the target well logging curve, and divide the formation boundary corresponding to each marker layer.

[0119] The preferred marker layer determination module 320 is used to configure a corresponding indicator weight for the quantitative indicator corresponding to each marker layer, and determine the recommendation coefficient corresponding to the marker layer according to the indicator weight; and select the target marker layer with the highest recommendation coefficient.

[0120] The standard well screening module 330 is used to determine the well characteristic data corresponding to all the target wells within a preset block range; and screen standard wells from the target wells according to the well characteristic data and preset standard well screening rules.

[0121] The correction amount determination module 340 is used to screen correction wells that have different logging curve values ​​from the standard wells in the target wells, and determine the curve correction amount corresponding to the correction wells based on the logging curve value corresponding to the target marker layer of the standard wells.

[0122] The standardization processing module is used to process the target logging curve according to the curve correction amount.

[0123] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference may be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0124] The embodiment of the present disclosure provides a logging curve standardization device, which obtains a target logging curve, determines a quantitative index for evaluating the characteristics of a marker layer corresponding to a target well according to the target logging curve, and divides the formation boundary corresponding to each marker layer; for each marker layer, configures a corresponding index weight for the quantitative index corresponding to the marker layer, and determines the recommended coefficient corresponding to the marker layer according to the index weight; selects the target marker layer with the highest recommended coefficient; determines the well characteristic data corresponding to all the target wells within a preset block range; selects standard wells in the target wells according to the well characteristic data and preset standard well screening rules; selects correction wells that have differences in logging curve values ​​from the standard wells in the target wells, and determines the curve correction amount corresponding to the correction well based on the logging curve value corresponding to the target marker layer of the standard well; and processes the target logging curve according to the curve correction amount. The accuracy and rationality of selecting standard wells and marker layers can be improved, and the accuracy of generating correction amounts in the process of standardizing logging curves can be improved.

[0125] Corresponds to Figure 1 The logging curve standardization method in the present disclosure also provides an electronic device 400, such as Figure 4 FIG. 4 is a schematic diagram of the structure of an electronic device 400 provided in an embodiment of the present disclosure, including:

[0126] Processor 41, memory 42, and bus 43; memory 42 is used to store execution instructions, including memory 421 and external memory 422; memory 421 here is also called internal memory, which is used to temporarily store operation data in processor 41 and data exchanged with external memory 422 such as hard disk. Processor 41 exchanges data with external memory 422 through memory 421. When the electronic device 400 is running, the processor 41 communicates with the memory 42 through bus 43, so that the processor 41 executes Figure 1 The steps of the well logging curve standardization method.

[0127] The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the well logging curve normalization method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0128] The present disclosure also provides a computer program product, which includes computer instructions. When the computer instructions are executed by a processor, the steps of the logging curve standardization method described in the above method embodiment can be executed. For details, please refer to the above method embodiment, which will not be repeated here.

[0129] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is implemented as a computer storage medium. In another optional embodiment, the computer program product is implemented as a software product, such as a software development kit (SDK).

[0130] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0132] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0133] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0134] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A logging curve normalization method, characterized in that, it includes: Obtain the target logging curve, and according to the target logging curve, determine the quantization index for evaluating the characteristics of the corresponding marker bed of the target well, and divide the formation boundaries corresponding to each marker bed; For each of the marker beds, configure a corresponding index weight for the quantization index corresponding to the marker bed, and determine the recommended coefficient corresponding to the marker bed according to the index weight; screen the target marker bed with the highest recommended coefficient; Determine the well characteristic data corresponding to all the target wells within the preset block range; According to the well characteristic data and the preset standard well screening rules, screen the standard wells among the target wells; Among the target wells, screen the correction wells with differences in logging curve values from the standard well, and take the logging curve value corresponding to the target marker bed of the standard well as the benchmark to determine the curve correction amount corresponding to the correction well; Process the target logging curve according to the curve correction amount.

2. The method according to claim 1, characterized in that, The step of determining the quantization index for evaluating the characteristics of the corresponding marker bed of the target well according to the target logging curve specifically includes: The marker bed characteristics include electrical characteristics, lateral distribution characteristics, and lithology characteristics; For the electrical characteristics, determine the mean similarity and variance similarity between the target logging curve and the logging curve of the preset reference well as the quantization index; For the lateral distribution characteristics, evaluate the curve similarity between the target logging curve and the logging curve of the preset reference well through dynamic time warping as the quantization index; For the lithology characteristics, determine the curve smoothness corresponding to the target logging curve as the quantization index.

3. The method according to claim 2, characterized in that, The step of, for each of the marker beds, configuring a corresponding index weight for the quantization index corresponding to the marker bed, and determining the recommended coefficient corresponding to the marker bed according to the index weight; screening the target marker bed with the highest recommended coefficient specifically includes: Construct an evaluation matrix for the marker bed in the corresponding index dimensions of the electrical characteristics, the lateral distribution characteristics, and the lithology characteristics; For each element in the evaluation matrix, configure a corresponding index score value for the element; According to the quantization index and the index score value, determine the index weight corresponding to the quantization index by the sum-product method or the square root method; Perform normalization summation on the index weight and the corresponding quantization index to determine the recommended coefficient; For each target well, sort the marker beds in descending order according to the recommended coefficient, and determine the marker bed with the highest recommended coefficient as the target marker bed corresponding to the target well.

4. The method according to claim 1, characterized in that, Obtain the marker beds of all wells within the preset block range based on the following steps: According to the structural type to which the target well belongs, set the minimum well spacing between the target well and the comparison well; For the comparison wells within the minimum well - to - well distance range, the principle of equal - thickness comparison is adopted. According to the thickness of the marker bed corresponding to the target marker bed, the top and bottom boundary depths of the marker bed of the comparison well are identified. For the comparison wells outside the minimum well - to - well distance range, according to the preset error range of the top and bottom boundary depths of the marker bed, the alternative depth area of the marker bed of the comparison well is determined. According to the similarity between the logging curves corresponding to the alternative depth area and the target logging curve, the curve similarity segments between the top and bottom boundary curves of the target marker bed in the logging curves corresponding to the comparison well and the target logging curve within the alternative depth area are determined. Among the curve similarity segments, the depths with the same curve values as the top and bottom boundary curves of the marker bed corresponding to the target well are selected as the top and bottom boundary depths of the marker bed corresponding to the comparison well.

5. The method according to claim 1, wherein, Based on the logging curve values corresponding to the target marker bed of the standard well, the curve correction amount corresponding to the correction well is determined, which specifically includes: For each target marker bed corresponding to the target well, the logging curve values are divided into multiple target segments. The frequencies of the logging curve values falling into each target segment are counted, and the logging value frequency distribution histogram corresponding to each target well is determined. The difference between the logging curve values corresponding to the maximum frequencies in the logging value frequency distribution histograms of the standard well and the correction well is determined. The difference is determined as the correction amount.

6. The method according to claim 1, wherein, After determining the curve correction amount corresponding to the correction well based on the logging curve values corresponding to the target marker bed of the standard well, the method further includes: Determining whether the difference between the standard well and the correction well is caused by the logging series. If so, the correction amount is applied to all wells under this logging series. If not, the correction amount corresponding to each well is applied to each well respectively.

7. The method according to claim 1, wherein, After processing the target logging curve according to the curve correction amount, the method further includes: Drawing the trend surface diagram corresponding to the correction amount, the relative error trend surface diagram, and the trend surface diagram corresponding to the logging curve values after correction.

8. A logging curve standardization device, wherein, comprising: A marker bed division module, configured to obtain a target logging curve, determine a quantitative index for evaluating the characteristics of the marker bed corresponding to the target well according to the target logging curve, and divide the formation boundaries corresponding to each marker bed. A preferred marker bed determination module, configured to, for each marker bed, configure a corresponding index weight for the quantitative index corresponding to the marker bed, and determine the recommended coefficient corresponding to the marker bed according to the index weight; screen the target marker bed with the highest recommended coefficient. A standard well screening module, configured to determine the well characteristic data corresponding to all the target wells within the preset block range. According to the well characteristic data and the preset standard well screening rules, a standard well is screened from the target wells. The correction amount determination module is configured to screen correction wells in the target well that have differences in logging curve values from the standard well, and determine the curve correction amount corresponding to the correction well based on the logging curve value corresponding to the target marker bed of the standard well; The normalization processing module is configured to process the target logging curve according to the curve correction amount.

9. An electronic device, Characterized in that, It includes: A processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the logging curve normalization method according to any one of claims 1 to 7 are executed.

10. A computer-readable storage medium, Characterized in that, A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of the logging curve normalization method according to any one of claims 1 to 7 are executed.

Images