Electric logging data normalization processing method and equipment based on XRD mineral constraint

Abstract

The invention provides an electric logging data normalization processing method and equipment based on X-ray diffraction (XRD) mineral constraint, and belongs to the field of petroleum logging engineering.The method comprises the steps that test data of mineral composition parameters and cable logging data of rock physical property parameters are obtained, and the mineral composition parameters at least comprise rock mineral composition obtained through X-ray diffraction testing; based on the test data of the mineral composition parameters, determining calculated values of the rock physical property parameters by utilizing a volume summation method; judging whether the calculated value of the rock physical property parameter is completely matched with the cable logging data of the rock physical property parameter or not; if the judgment result is incomplete matching, performing normalization processing on the cable logging data of the rock physical property parameters based on the calculated values of the rock physical property parameters; otherwise, the normalization processing is not carried out. Through the method provided by the invention, all system errors of the cable test data can be reduced, so that the cable logging information can more accurately reflect the physical properties of underground rocks.

Description

Technical Field

[0001] This invention relates to the field of oil well logging engineering technology, specifically to a method for normalizing electrical logging data based on XRD mineral constraints, a device for normalizing electrical logging data based on XRD mineral constraints, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Wireline logging is widely used to estimate the properties of subsurface rocks. Compared to laboratory testing using core samples collected from wells, wireline logging is cheaper and provides a denser dataset. However, in addition to being influenced by rock properties, wireline logging results are also affected by logging tools, operating conditions, and processing methods. Even within the same well, wireline logging results from different tools and companies can vary, or systematic errors may exist between different wells. Therefore, normalization of wireline logging data is crucial for subsurface rock analysis. Summary of the Invention

[0003] To address the technical problem of systematic errors in existing cable logging data, this invention provides a method for normalizing cable logging data based on XRD mineral constraints. This method can reduce all systematic errors in cable logging data, enabling cable logging data to more accurately reflect the physical properties of underground rocks.

[0004] To achieve the above objectives, the first aspect of the present invention provides a method for normalizing electrical logging data based on XRD mineral constraints. This method includes the following steps: acquiring test data of mineral composition parameters and wireline logging data of rock physical property parameters, wherein the mineral composition parameters include at least the rock mineral composition obtained from X-ray diffraction testing; determining the calculated values ​​of the rock physical property parameters based on the test data of the mineral composition parameters using the volume summation method; determining whether the calculated values ​​of the rock physical property parameters and the wireline logging data of the rock physical property parameters are completely matched; if the determination result is not a complete match, normalizing the wireline logging data of the rock physical property parameters based on the calculated values ​​of the rock physical property parameters; and if the determination result is a complete match, not normalizing the wireline logging data of the rock physical property parameters.

[0005] In an exemplary embodiment of the present invention, the determination of the calculated values ​​of rock physical property parameters based on test data of mineral composition parameters using the volume summation method may include: determining the rock physical property parameters under different rock mineral composition conditions; and determining the calculated values ​​of the rock physical property parameters based on the rock physical property parameters under different rock mineral composition conditions using the volume summation method.

[0006] In an exemplary embodiment of the present invention, the mineral composition parameter may further include: porosity at the same test depth as the rock mineral composition;

[0007] The calculation of rock physical property parameters based on test data of mineral composition parameters using the volume summation method may include: determining rock physical property parameters under different rock mineral composition conditions and different porosity conditions; and determining the calculated values ​​of rock physical property parameters based on rock physical property parameters under different rock mineral composition conditions and different porosity conditions using the volume summation method.

[0008] In an exemplary embodiment of the present invention, the mineral composition parameters may further include: organic matter, and porosity at the same test depth as the rock mineral composition;

[0009] The calculation of rock physical property parameters based on test data of mineral composition parameters using the volume summation method may include: determining rock physical property parameters under different rock mineral composition conditions, different porosity conditions, and different organic matter conditions; and determining the calculated values ​​of rock physical property parameters using the volume summation method based on rock physical property parameters under different rock mineral composition conditions, different porosity conditions, and different organic matter conditions.

[0010] In an exemplary embodiment of the present invention, the rock physical properties may include: gamma rays, density, thermal neutron porosity, and photoelectric factor.

[0011] In one exemplary embodiment of the present invention, the calculated value of gamma rays can be determined according to the following formula:

[0012]

[0013] Among them, GR calculated Gamma rays calculated based on test data of mineral composition parameters; GR i V is the gamma value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

[0014] In an exemplary embodiment of the present invention, the calculated value of density can be determined according to the following formula:

[0015]

[0016] Among them, RHOB calculated The density is calculated based on test data of mineral composition parameters; RHOB i V is the density value determined based on the i-th set of test values ​​of mineral composition parameters; iLet i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

[0017] In an exemplary embodiment of the present invention, the calculated value of thermal neutron porosity can be determined according to the following formula:

[0018]

[0019] Among them, NPHI calculated Thermal neutron porosity calculated based on test data of mineral composition parameters; HI i V is the hydrogen index value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

[0020] In an exemplary embodiment of the present invention, the calculated value of the photoelectric factor can be determined according to the following formula:

[0021]

[0022] Among them, PEF calculated The photoelectric factor (PEF) is calculated based on test data of mineral composition parameters. i V is the photoelectric factor value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

[0023] In an exemplary embodiment of the present invention, determining whether the calculated values ​​of rock physical property parameters and the wireline logging data of rock physical property parameters are completely matched may include: plotting the calculated values ​​of rock physical property parameters as theoretical calculation curves, and plotting the wireline logging data of rock physical property parameters as actual logging curves; determining whether the theoretical calculation curves and actual logging curves show similar increasing or decreasing trends within the same depth range; if it is determined that the theoretical calculation curves and actual logging curves show dissimilar increasing or decreasing trends within the same depth range, outputting a determination result indicating that the calculated values ​​of rock physical property parameters and the wireline logging data of rock physical property parameters are not completely matched; if it is determined that the theoretical calculation curves and actual logging curves show dissimilar increasing or decreasing trends within the same depth range, outputting a determination result indicating that the calculated values ​​of rock physical property parameters and the wireline logging data of rock physical property parameters are not completely matched; When similar increasing or decreasing trends are observed within the same depth range, the matching degree between the theoretical calculation curve and the actual logging curve is determined; the matching degree and matching degree threshold of the theoretical calculation curve and the actual logging curve within the same depth range are compared; if the matching degree of the theoretical calculation curve and the actual logging curve is greater than the matching degree threshold in some depth ranges, the judgment result that the calculated value of the rock physical property parameter does not completely match the wireline logging data of the rock physical property parameter is output; if the matching degree of the theoretical calculation curve and the actual logging curve is less than or equal to the matching degree threshold in all depth ranges, the judgment result that the calculated value of the rock physical property parameter completely matches the wireline logging data of the rock physical property parameter is output.

[0024] In an exemplary embodiment of the present invention, determining whether the theoretically calculated curve and the actual logging curve exhibit similar increasing or decreasing trends within the same depth range may include: determining the correlation coefficient between the theoretically calculated curve and the actual logging curve within the same depth range; comparing the correlation coefficient between the theoretically calculated curve and the actual logging curve within the same depth range with a correlation coefficient threshold; if the correlation coefficient between the theoretically calculated curve and the actual logging curve within the same depth range is greater than the correlation coefficient threshold, outputting a judgment result indicating that the theoretically calculated curve and the actual logging curve exhibit dissimilar increasing or decreasing trends within the same depth range; if the correlation coefficient between the theoretically calculated curve and the actual logging curve within the same depth range is less than or equal to the correlation coefficient threshold, outputting a judgment result indicating that the theoretically calculated curve and the actual logging curve exhibit similar increasing or decreasing trends within the same depth range.

[0025] In an exemplary embodiment of the present invention, the degree of matching between the theoretically calculated curve and the actual logging curve within the same depth range can be determined by calculating the root mean square error, the mean absolute error, and / or the standard deviation.

[0026] In an exemplary embodiment of the present invention, the normalization processing of the wireline logging data of rock physical parameters based on the calculated values ​​of rock physical parameters includes: determining, based on the judgment result, a data region where the calculated values ​​of rock physical parameters and the wireline logging data of rock physical parameters do not completely match; determining, based on the data region where the calculated values ​​of rock physical parameters and the wireline logging data of rock physical parameters do not completely match, the average error between the calculated values ​​of rock physical parameters and the wireline logging values ​​of rock physical parameters; and normalizing the wireline logging data of rock physical parameters based on the average error between the calculated values ​​of rock physical parameters and the wireline logging values ​​of rock physical parameters.

[0027] A second aspect of the present invention provides an XRD-based mineral-constrained electrical logging data normalization processing device, the normalization processing device comprising: an acquisition module for acquiring test data of mineral composition parameters and wireline logging data of rock physical property parameters, wherein the mineral composition parameters include at least the rock mineral composition obtained by X-ray diffraction testing; a determination module for determining the calculated values ​​of rock physical property parameters based on the test data of mineral composition parameters using the volume summation method; a judgment module for judging whether the calculated values ​​of rock physical property parameters and the wireline logging data of rock physical property parameters are completely matched; and a processing module for performing normalization processing on the wireline logging data of rock physical property parameters based on the calculated values ​​of rock physical property parameters when the judgment result is not completely matched; and for not performing normalization processing on the wireline logging data of rock physical property parameters when the judgment result is completely matched.

[0028] A third aspect of the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores at least one computer program, the at least one computer program being loaded and executed by one or more of the processors to cause the processors to perform the XRD mineral-constrained electrical logging data normalization processing method as described above.

[0029] A fourth aspect of the present invention provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to enable a computer to perform the XRD mineral-constrained electrical logging data normalization processing method as described above.

[0030] The present invention has at least the following technical effects through the technical solution provided by the present invention:

[0031] (1) The XRD mineral-constrained normalization processing method for electrical logging data of the present invention innovatively uses the minerals tested by XRD to constrain the logging normalization, which not only makes the normalized logging curve have a substantial correspondence with the physical properties of the rock, but also reduces all systematic errors in the electrical logging results, so that the electrical logging results can more accurately reflect the physical properties of the underground rock.

[0032] (2) The XRD-based mineral-constrained electrical logging data normalization processing method of the present invention helps logging personnel to recognize and discover the limitations of electrical logging results, thereby understanding the physical properties of the actual formation. Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0033] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0034] Figure 1 This is a flowchart illustrating the method for normalizing electrical logging data based on XRD mineral constraints provided in an embodiment of the present invention.

[0035] Figure 2 A comparison chart of theoretical calculation curves and actual well logging curves for the Chang 73 Shale in the Ordos Basin provided in this embodiment of the invention;

[0036] Figure 3 A comparison chart of the theoretical calculation curve and the normalized actual logging curve of the Chang 73 Shale in the Ordos Basin provided in this embodiment of the invention.

[0037] Figure 4 A comparison chart of theoretical calculation curves and actual logging curves for the Wolfcamp shale well in the eastern Permian Basin provided for an embodiment of the present invention;

[0038] Figure 5 A comparison chart of theoretical calculation curves and actual logging curves for the Wolfcamp shale well in the western part of the Eastern Permian Basin, provided for an embodiment of the present invention;

[0039] Figure 6 A comparison chart of the theoretical calculation curve and the normalized actual logging curve of the Wolfcamp shale well in the western part of the East Permian Basin provided for embodiments of the present invention.

[0040] Figure 7 A schematic diagram of the structure of the XRD-based mineral-constrained electrical logging data normalization processing device provided in an embodiment of the present invention;

[0041] Figure 8This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0042] Explanation of reference numerals in the attached figures

[0043] 101-Acquisition module, 102-Determination module, 103-Judgment module, 104-Processing module, 201-Processor, 202-Memory. Detailed Implementation

[0044] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0045] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0046] In this invention, terms such as "first" and "second" are used merely for ease of description and distinction, and should not be construed as indicating or implying relative importance.

[0047] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integrated connection; they can refer to a direct connection or an indirect connection; they can refer to a wired connection or a wireless connection. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0048] In existing technologies, the normalization process for well logging data generally involves calculating the ratio of the logging data at each point to the maximum value of the curve in the well section, thereby making the data quantitatively comparable and normalizing the curves and data. While these methods can standardize well logging data, they cannot completely reduce all systematic errors in the well logging data.

[0049] Considering the systematic errors in existing wireline logging data, this invention proposes a normalization method for wireline logging data based on XRD mineral constraints. This method, given known physical properties such as gamma rays, density, thermal neutron porosity, and photoelectric factor, can calculate the physical properties of rocks using a volume summation method. If these calculated rock properties match the relevant wireline logging data, no normalization is needed; however, if they do not match, normalization is required to match the calculated rock physical properties. Compared to existing normalization methods, this improves the accuracy of wireline logging data. In practical implementation, this method can be executed by electronic equipment, such as servers or terminals with processing capabilities.

[0050] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings and embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0051] like Figure 1 As shown in the figure, this invention provides a method for normalizing electrical logging data based on XRD mineral constraints. The method includes the following steps:

[0052] Step S101: Obtain test data of mineral composition parameters and wireline logging data of rock physical property parameters.

[0053] The mineral composition parameters include at least the rock mineral composition obtained from X-ray diffraction testing.

[0054] It should be noted that X-ray diffraction (XRD) is a technique widely used in materials science and geology to determine the structure and composition of crystalline materials. In geology, XRD is often used to analyze the mineral composition of rock samples. The data obtained from XRD tests are typically diffraction patterns, which contain the scattering patterns of X-rays by the sample. By analyzing these patterns, the types and relative abundance of minerals present in the sample can be determined.

[0055] Step S102: Based on the test data of mineral composition parameters, determine the rock composition using the volume summation method.

[0056] Calculated values ​​of physical property parameters.

[0057] Step S103: Determine whether the calculated values ​​of rock physical property parameters are completely matched with the wireline logging data of rock physical property parameters.

[0058] Step S104: If the judgment result is not a complete match, the wireline logging data of the rock physical parameters are normalized based on the calculated values ​​of the rock physical parameters.

[0059] Step S105: If the judgment result is a complete match, no normalization processing is performed on the cable logging data for rock physical parameters.

[0060] Furthermore, in one possible implementation, the rock physical properties may include one or more of gamma rays, density, thermal neutron porosity, and photoelectric factor.

[0061] Of course, the present invention is not limited to this. Other rock physical properties such as acoustic wave, resistivity, and magnetic susceptibility are also applicable to the XRD mineral-constrained electrical logging data normalization processing method in the embodiments of the present invention.

[0062] Furthermore, in one possible implementation, when the mineral composition parameters only include the rock mineral composition, the process of determining the calculated values ​​of the rock physical property parameters in step S102 based on the test data of the mineral composition parameters using the volume summation method may include, but is not limited to, the following sub-steps S1021A to S1022A.

[0063] Sub-step S1021A determines the rock physical property parameters under different rock mineral composition conditions.

[0064] Sub-step S1022A: Based on the rock physical property parameters under different rock mineral composition conditions, the calculated values ​​of the rock physical property parameters are determined using the volume summation method.

[0065] Furthermore, in another possible implementation, in addition to the rock mineral composition obtained from XRD testing, the influence of porosity on rock physical property parameters also needs to be considered when calculating these parameters based on the test data of mineral composition parameters. If porosity is tested at the same depth as the mineral composition test, then the physical properties of the rock (i.e., rock physical property parameters) can be directly calculated from the test data of rock mineral composition and porosity. However, in actual well logging, porosity is often only obtained at depths that do not match the rock mineral composition test depth, or no porosity is obtained at all. In this case, porosity can be determined in other ways. For example, one way to determine porosity is to assume a porosity value or a set of porosity values ​​(e.g., 5%–9%) to account for the uncertainty caused by the lack of porosity. Another way to determine porosity is to estimate a porosity value or a set of porosity values ​​using other methods such as density logging, linear regression, etc.

[0066] In other words, in addition to the rock mineral composition, the mineral composition parameters can also include porosity at the same test depth as the rock mineral composition.

[0067] Therefore, in step S102, the process of determining the calculated values ​​of rock physical property parameters based on the test data of mineral composition parameters using the volume summation method may also include, but is not limited to, the following sub-steps S1021B to S1022B.

[0068] Sub-step S1021B determines the rock physical property parameters under different rock mineral composition conditions and different porosity conditions.

[0069] Sub-step S1022B: Based on the rock physical property parameters under different rock mineral composition conditions and different porosity conditions, the calculated values ​​of the rock physical property parameters are determined by the volume summation method.

[0070] Furthermore, in another possible implementation, in addition to rock mineral composition and porosity, the influence of organic matter on rock physical properties needs to be considered when calculating rock physical properties based on test data of mineral composition parameters. Organic matter is common in shale formations and coal, but not in other lithologies; therefore, only shale and coal require consideration of organic matter. If organic matter is present in the rock but test data is unavailable, the same strategy as for porosity can be used to determine test data for organic matter through assumptions or estimations. The difference from porosity is that the physical properties of organic matter can vary significantly due to the influence of sedimentary environment and thermal maturation. For example, the degree of hydrocarbon generation under different thermal maturation conditions leads to differences in the density and hydrogen index of organic matter. Furthermore, the gamma rays of organic matter show significant differences between different basins or different shale formations within the same basin. Therefore, during normalization, different values ​​for organic matter's gamma rays, density, neutron porosity, etc., need to be considered and tested.

[0071] In other words, mineral composition parameters include not only rock mineral composition and porosity, but also...

[0072] This further includes organic matter.

[0073] Therefore, in step S102, the process of determining the calculated values ​​of rock physical property parameters based on the test data of mineral composition parameters using the volume summation method may also include, but is not limited to, the following sub-steps S1021C to S1022C.

[0074] Sub-step S1021C determines the rock physical property parameters under different rock mineral composition conditions, different porosity conditions, and different organic matter conditions.

[0075] Sub-step S1022C: Based on rock physical property parameters under different rock mineral composition conditions, different porosity conditions, and different organic matter conditions, the calculated values ​​of rock physical property parameters are determined using the volume summation method.

[0076] It should be noted that this invention is not limited to this. In addition to considering the influence of rock mineral composition, porosity, and organic matter on rock physical property parameters, other influencing factors can also be considered. Pores in the formation can be filled by one or more of oil, gas, and water. When the fluids in the pores are different, the physical properties of the rocks will be different, but this difference is usually small. Therefore, in many cases, due to the lack of saturation data or inaccurate core testing, the fluid in the pores can be simplified to water. This will affect the calculated values ​​of rock physical property parameters, but it is generally small and can usually be ignored. However, if saturation data is available, the volume ratio of various fluids can be known, i.e., Vi in the following formulas (1) to (4). For example, if the saturation measured in the laboratory is available or can be estimated, the influence of fluid saturation on rock physical property parameters can also be considered in the process of calculating rock physical property parameters based on the test data of mineral composition parameters. It is worth noting that the presence of oil will not change most of the rock property calculations except for resistivity, and the presence of gas has a small effect on resistivity, density, sound velocity, and neutron porosity.

[0077] Furthermore, although minerals, organic matter, and porosity are the main components of rocks, mineral composition parameters can be mainly classified into three types: rock mineral composition, porosity, and organic matter. However, each parameter can be further subdivided into other parameters. For example, a mineral can contain many different types of minerals.

[0078] Furthermore, in one possible implementation, it can be done according to the following formulas (1) to (4).

[0079] Determine the calculated values ​​of rock physical property parameters.

[0080]

[0081]

[0082]

[0083]

[0084] In the formula, i represents the nth set of test values ​​for the mineral composition parameter, which can include rock mineral composition, rock mineral composition and porosity, or rock mineral composition, porosity and organic matter (if present); 1≤i≤N, where N represents the total number of sets of test values ​​for the mineral composition parameter; GR calculated Gamma rays are calculated based on mineral properties and mineral concentration (i.e., test data of mineral composition parameters); GR i RHOB represents the gamma value determined based on the i-th set of test values ​​of mineral composition parameters. calculatedThe density is calculated based on mineral properties and mineral concentration (i.e., test data of mineral composition parameters); RHOB i The density value determined based on the i-th set of test values ​​of mineral composition parameters; NPHI calculated Thermal neutron porosity is calculated based on mineral properties and mineral concentration (i.e., test data of mineral composition parameters); HI i The hydrogen index value determined based on the i-th set of test values ​​of mineral composition parameters; PEF calculated The photoelectric factor (PEF) is calculated based on mineral properties and mineral concentration (i.e., test data of mineral composition parameters). i V is the photoelectric factor value determined based on the i-th set of test values ​​of mineral composition parameters; i is the rock volume value corresponding to the i-th set of test values ​​of mineral composition parameters.

[0085] It should be noted that the photoelectric factor (PEF) calculated The calculation equations for ) and three other rock physical parameters (GR) calculated RHOB calculated NPHI calculated The reason for the different calculation equations is that the volume measurement of the photoelectric factor is not based on a single electron, but on the target (effective cross section in the nuclear interaction related to the incident particle) per unit volume. Therefore, it is necessary to multiply the photoelectric factor by the density to convert it into the photoelectric factor per unit volume.

[0086] Furthermore, in practice, the assumed porosity and porosity estimated by other methods are generally inaccurate, leading to discrepancies between the calculated rock physical properties based on XRD minerals and the actual values. To achieve greater accuracy, iterative calculations may sometimes be necessary to make the results more reliable.

[0087] Furthermore, in one possible implementation, the process of determining whether the calculated value of the rock physical property parameter and the wireline logging data of the rock physical property parameter are completely matched in step S103 may include, but is not limited to, the following sub-steps S1031 to S1037.

[0088] Sub-step S1031: Plot the calculated values ​​of rock physical parameters as theoretical calculation curves, and plot the wireline logging data of rock physical parameters as actual logging curves.

[0089] Sub-step S1032 determines whether the theoretically calculated curve and the actual logging curve show similar increasing or decreasing trends within the same depth range.

[0090] Sub-step S1033: If the theoretical calculation curve and the actual logging curve show dissimilar increasing or decreasing trends within the same depth range, output the judgment result that the calculated value of the rock physical property parameter does not completely match the wireline logging data of the rock physical property parameter.

[0091] Sub-step S1034: If the theoretical calculation curve and the actual logging curve show similar increasing or decreasing trends within the same depth range, determine the matching degree between the theoretical calculation curve and the actual logging curve within the same depth range.

[0092] Sub-step S1035 compares the matching degree and matching degree threshold between the theoretically calculated curve and the actual logging curve within the same depth range.

[0093] Sub-step S1036: If the degree of matching between the theoretical calculation curve and the actual logging curve is greater than the matching threshold in a certain depth range, output the judgment result that the calculated value of the rock physical property parameter does not completely match the wireline logging data of the rock physical property parameter.

[0094] Sub-step S1037: If the matching degree between the theoretical calculation curve and the actual logging curve is less than or equal to the matching degree threshold in the entire depth range, output the judgment result that the calculated value of the rock physical property parameter is completely matched with the wireline logging data of the rock physical property parameter.

[0095] Of course, this invention is not limited to this. It is also possible to directly determine whether the calculated values ​​of rock physical property parameters completely match the wireline logging data of rock physical property parameters by observing the increasing and decreasing trends of the theoretical calculation curve and the actual logging curve. If the theoretical calculation curve and the actual logging curve basically overlap, or if the peak values ​​of the theoretical calculation curve and the actual logging curve within the same increasing and decreasing trend are not significantly different (e.g., the difference between the maximum (or minimum) value of the theoretical calculation curve and the maximum (or minimum) value of the actual logging curve is less than a predetermined threshold), then it can be considered that the calculated values ​​of rock physical property parameters completely match the wireline logging data of rock physical property parameters; conversely, it can be considered that the calculated values ​​of rock physical property parameters do not completely match the wireline logging data of rock physical property parameters.

[0096] Furthermore, in one possible implementation, the specific implementation process of determining whether the theoretical calculation curve and the actual logging curve show similar increasing or decreasing trends within the same depth range in sub-step S1032 may include the following steps:

[0097] (1) Determine the correlation coefficient between the theoretical calculation curve and the actual logging curve within the same depth range;

[0098] (2) Compare the correlation coefficient and correlation coefficient threshold of the theoretically calculated curve and the actual logging curve within the same depth range;

[0099] (3) If the correlation coefficient between the theoretical calculation curve and the actual logging curve is greater than the correlation coefficient threshold within the same depth range, output the judgment result that the theoretical calculation curve and the actual logging curve show dissimilar increasing or decreasing trends within the same depth range;

[0100] (4) If the correlation coefficient between the theoretical calculation curve and the actual logging curve is less than or equal to the correlation coefficient threshold within the same depth range, output the judgment result that the theoretical calculation curve and the actual logging curve show similar increasing or decreasing trends within the same depth range.

[0101] Of course, this invention is not limited to this. Other methods can also be used to determine whether theoretically calculated curves and actual logging curves exhibit similar increasing or decreasing trends within the same depth range. For example, by comparing the rate of change (i.e., slope) and direction of change of the two sets of curves within the same depth range, if the rate of change (i.e., slope) of the two sets of curves within the same depth range is less than a preset rate of change threshold and the direction of change is consistent, then the theoretically calculated curve and the actual logging curve can be considered to exhibit similar increasing or decreasing trends within the same depth range. Conversely, if the rate of change (i.e., slope) of the two sets of curves within the same depth range is less than a preset rate of change threshold and the direction of change is consistent, then the theoretically calculated curve and the actual logging curve can be considered to exhibit similar increasing or decreasing trends within the same depth range.

[0102] They exhibit dissimilar trends of increase and decrease within a certain range.

[0103] Furthermore, in one possible implementation, in sub-step S1034, the degree of matching between the theoretical calculation curve and the actual logging curve within the same depth range can be determined by calculating the root mean square error, mean absolute error, and / or standard deviation.

[0104] For example, the root mean square error, mean absolute error, or standard deviation can be directly calculated, and the results can be used to determine the degree of matching between the theoretical calculation curve and the actual logging curve within the same depth range.

[0105] For example, the root mean square error, mean absolute error, and standard deviation can be calculated separately, and each of these can be assigned a weight value. Then, the root mean square error, mean absolute error, and standard deviation can be multiplied by their respective weight values ​​to obtain the scores for the three types of errors. Finally, by summing the scores for the three types of errors, the degree of matching between the theoretical calculation curve and the actual logging curve within the same depth range can be determined.

[0106] Here, the specific calculation method for the root mean square error is as follows: calculate the square of the difference between each corresponding point, then take the average and then take the square root. The specific calculation method for the mean absolute error is as follows: calculate the average of the absolute values ​​of the differences between each data point. The specific calculation method for the standard deviation is as follows: first, calculate the mean of the dataset; then, calculate the difference between each data point and the mean, then calculate the square of this difference to obtain the mean deviation; then calculate the average of the mean deviations to obtain the variance; finally, take the square root of the variance to obtain the standard deviation.

[0107] Furthermore, in one possible implementation, in step S104, when the judgment result is not a complete match, the process of normalizing the wireline logging data of rock physical parameters based on the calculated values ​​of rock physical parameters may include, but is not limited to, the following sub-steps S1041 to S1043.

[0108] Sub-step S1041: Based on the judgment result, determine the data area where the calculated values ​​of rock physical property parameters do not completely match the wireline logging data of rock physical property parameters.

[0109] Sub-step S1042: Based on the data region where the calculated values ​​of rock physical property parameters do not completely match the wireline logging data of rock physical property parameters, determine the relationship between the calculated values ​​and the actual values ​​of rock physical property parameters.

[0110] The average error of cable logging values.

[0111] Sub-step S1043: Based on the average error between the calculated values ​​of rock physical parameters and the wireline logging values ​​of rock physical parameters, normalize the wireline logging data of rock physical parameters.

[0112] Of course, the present invention is not limited to this. Based on the calculated values ​​of rock physical parameters, the normalization processing of wireline logging data for rock physical parameters can also be carried out in the following way: After plotting the calculated values ​​of rock physical parameters and wireline logging data as theoretical calculation curves and actual logging curves respectively, firstly, identify the areas where there is a mismatch between the theoretical calculation curve and the actual logging curve; then, based on the areas where there is a mismatch between the theoretical calculation curve and the actual logging curve, calculate the numerical range in which the actual logging curve should be scaled or shifted; finally, based on the calculated numerical range in which it should be scaled or shifted, perform the corresponding scaling or translation operation on the entire actual logging curve.

[0113] To verify the effectiveness and practicality of the XRD mineral-constrained electrical logging data normalization method of the present invention, the Chang 73 shale well in the Ordos Basin and the Wolfcamp shale well in the Eastern Permian Basin were used as examples. The XRD mineral-constrained electrical logging data normalization method of the present invention was implemented for these two wells to achieve the normalization of the wireline logging data.

[0114] Figure 2 A comparison of the theoretical calculation curve and the normalized actual well logging curve for the Chang 73 shale in the Ordos Basin. Figure 3 This is a comparison chart of the theoretical calculation curve and the actual logging curve after normalization for the Chang 73 shale in the Ordos Basin.

[0115] in, Figure 2 The continuous curve in the figure represents the actual logging curve plotted based on wireline logging data of rock physical properties. Figure 3 The continuous curve in the figure represents the actual logging curve after normalization. Figure 2 and Figure 3 The numerical points in the table represent the calculated values ​​of rock physical property parameters obtained using formulas (1) to (4).

[0116] like Figure 2 As shown, there are significant differences between the actual electrical logging curves and the gamma ray, density, and thermal neutron porosity values ​​calculated using mineral composition. Specifically, the measured thermal neutron porosity curve (NPHI) is consistently larger than the neutron porosity curve calculated using mineral composition. The gamma ray (GR) and density curves (RHOB) match in the upper part of the profile but do not match in the lower part.

[0117] like Figure 3 As shown, the measured electrical logging curve obtained by dividing the thermal neutron porosity curve by 1.5 matches the calculated value of thermal neutron porosity, and the measured electrical logging curve obtained by dividing the density curve by 2 and adding 1.25 matches the calculated value of density. However, due to the abnormally high value at the bottom of the gamma curve, no simple scaling or shifting method can perfectly match the gamma curve and its calculated value.

[0118] Figure 4 A comparison of theoretical calculation curves and actual logging curves for the Wolfcamp shale well in the eastern part of the Eastern Permian Basin; Figure 5 A comparison of theoretical calculation curves and actual logging curves for the Wolfcamp shale well in the western part of the Eastern Permian Basin; Figure 6 This is a comparison chart of the theoretical calculation curves and the normalized actual logging curves for the Wolfcamp shale well in the western part of the Eastern Permian Basin. Figure 4 and Figure 5The continuous curve in the figure represents the actual logging curve plotted based on wireline logging data of rock physical properties. Figure 6 The continuous curve in the figure represents the actual logging curve after normalization. Figure 4 , Figure 5 and Figure 6 The numerical points in the table represent the calculated values ​​of rock physical property parameters obtained using formulas (1) to (4).

[0119] like Figure 4 As shown, in a well in the Wolfcamp Shale in the eastern Permian Basin, the actual logging curves and calculated logging curves show good agreement. Therefore, normalization is not required. However, in Figure 5 In the Middle Permian, significant differences exist between the actual and calculated well logging curves of the Wolfcamp Shale in the western Wolfcamp Shale, particularly in gamma ray (GR) and photoelectric factor (PEF). For the gamma ray curve, the calculated minimum value is larger than the measured minimum, and the maximum value is smaller. The measured PEF is consistently larger than the calculated PEF. Therefore, normalization of gamma rays and PEF is necessary.

[0120] like Figure 6 As shown, the normalized logging curves result in a better match between the actual cable logging curves and their calculated values.

[0121] Furthermore, when very thin strata exist within a formation (typically thin layers of volcanic ash and limestone in shale), well logging values ​​cannot accurately reflect the actual physical properties of the formation, while XRD testing can accurately reflect the mineral content of the formation. This leads to discrepancies between well logging data and calculated rock physical properties at thin-layer locations. On the well logging profile, this manifests as most of the rock physical properties calculated by XRD matching the well logging data, but not at some sharp peaks in the logging data. Therefore, the calculated mineral gamma ray can also help understand the limitations of gamma ray logging in this well, namely, a large number of...

[0122] Thin layers rich in quartz and calcite cannot be effectively identified by gamma logging.

[0123] In summary, compared with other normalization methods, the present invention has significant advantages in normalizing relevant logging curves using calculated rock properties. This is due to the close correlation between logging response and rock properties. Ideally, logging curves record the correct measurements of rock properties (e.g., gamma rays, density). However, in practical applications, due to factors such as logging tool calibration, logging environment, and data processing, logging curves may deviate from the true properties of the rock. For example, Figure 2 The neutron porosity curve in the sample is significantly larger than the neutron porosity calculated from the mineral. Figure 5The photoelectric factor in the calculated rock properties is significantly greater than that calculated from the mineral composition. Without these rock properties calculated from the mineral composition, it would be impossible to check whether the wireline logging correctly measured the rock properties. This is the most important advantage exhibited by the normalization method of this invention. Furthermore, the rock properties calculated from the mineral composition can help identify and recognize the limitations of wireline logging, such as… Figure 6 Thin layers rich in quartz and calcite that were missed in the study.

[0124] Furthermore, the implementation environment of this embodiment includes at least one terminal and one server, and the method is executed on the terminal or the server respectively. The terminal and the server can establish a communication connection to achieve interactive information transmission.

[0125] The terminal can be any electronic product that can interact with the user through one or more methods such as keyboard, touchpad, touch screen, voice interaction, etc., such as PC (Personal Computer), PPC (Pocket Personal Computer), tablet computer, etc.

[0126] A server can be a single server, a server cluster consisting of multiple servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0127] like Figure 7 As shown, this embodiment of the invention also provides a normalization processing device for electrical logging data based on XRD mineral constraints. The device includes: an acquisition module 101, a determination module 102, a judgment module 103, and a processing module 104.

[0128] The acquisition module 101 is used to acquire test data of mineral composition parameters and wireline logging data of rock physical property parameters. The mineral composition parameters include at least the rock mineral composition obtained from X-ray diffraction testing.

[0129] The determination module 102 is used to determine the calculated values ​​of rock physical property parameters based on test data of mineral composition parameters using the volume summation method.

[0130] The judgment module 103 is used to determine whether the calculated values ​​of rock physical property parameters are completely matched with the wireline logging data of rock physical property parameters.

[0131] The first processing module 104 is used to normalize the cable logging data based on the calculated values ​​of rock physical parameters when the judgment result is not a complete match; and not to normalize the cable logging data based on rock physical parameters when the judgment result is a complete match.

[0132] It should be noted that the above-described device is only illustrated by the division of the functional modules described above. In practical applications, the functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the device and method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0133] like Figure 8 As shown, this embodiment of the invention also provides an electronic device, which includes a processor 201 and a memory 202. The memory stores at least one computer program, which is loaded and executed by one or more of the processors to enable the processors to implement the XRD mineral constraint-based electrical logging data normalization processing method in the above embodiments.

[0134] Of course, the electronic device may also have wired or wireless network interfaces, keyboards, and input / output interfaces for input and output. The electronic device may also include other components for implementing the various functions of the device, which will not be elaborated here.

[0135] This invention also provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to enable a computer to implement the XRD mineral constraint-based electrical logging data normalization processing method described in the above embodiments.

[0136] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, or an optical disc data storage device, etc. Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in each embodiment of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc.

[0137] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0138] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0139] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for normalizing electrical logging data based on XRD mineral constraints, characterized in that, The normalization method includes: Cable logging data for obtaining mineral composition parameters and rock physical property parameters, wherein the mineral composition parameters include at least: rock mineral composition obtained by X-ray diffraction testing; Based on the test data of mineral composition parameters, the calculated values ​​of rock physical property parameters are determined using the volume summation method; Determine whether the calculated values ​​of rock physical property parameters match the wireline logging data of rock physical property parameters completely; In cases where the judgment result is not a complete match, the wireline logging data for the rock physical parameters are normalized based on the calculated values ​​of the rock physical parameters. If the judgment result is a perfect match, the cable logging data for rock physical parameters will not be normalized.

2. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 1, characterized in that, The calculated values ​​of rock physical properties are determined using the volume summation method based on the test data of mineral composition parameters, including: Determine the physical properties of rocks under different rock mineral compositions; Based on the rock physical property parameters under different rock and mineral composition conditions, the calculated values ​​of the rock physical property parameters are determined by the volume summation method.

3. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 1, characterized in that, The mineral composition parameters also include: porosity at the same test depth as the rock mineral composition; The calculated values ​​of rock physical properties are determined using the volume summation method based on the test data of mineral composition parameters, including: Determine the physical properties of rocks under different mineral composition and porosity conditions; Based on rock physical property parameters under different rock mineral composition and porosity conditions, the calculated values ​​of rock physical property parameters are determined using the volume summation method.

4. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 1, characterized in that, The mineral composition parameters also include: organic matter, and porosity at the same test depth as the rock mineral composition; The calculated values ​​of rock physical properties are determined using the volume summation method based on the test data of mineral composition parameters, including: Determine the physical properties of rocks under different mineral composition conditions, different porosity conditions, and different organic matter conditions; Based on rock physical property parameters under different rock mineral composition conditions, different porosity conditions, and different organic matter conditions, the calculated values ​​of rock physical property parameters are determined using the volume summation method.

5. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 2, 3, or 4, characterized in that, The rock physical properties include gamma rays, density, thermal neutron porosity, and photoelectric factor.

6. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 5, characterized in that, The calculated value of gamma rays is determined using the following formula: Among them, GR calculated Gamma rays calculated based on test data of mineral composition parameters; GR i V is the gamma value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

7. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 5, characterized in that, The calculated value of density is determined using the following formula: Among them, RHOB calculated The density is calculated based on test data of mineral composition parameters; RHOB i V is the density value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

8. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 5, characterized in that, The calculated value of thermal neutron porosity is determined using the following formula: Among them, NPHI calculated Thermal neutron porosity calculated based on test data of mineral composition parameters; HI i V is the hydrogen index value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

9. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 5, characterized in that, The calculated value of the photoelectric factor is determined according to the following formula: Among them, PEF calculated The photoelectric factor (PEF) is calculated based on test data of mineral composition parameters. i V is the photoelectric factor value determined based on the i-th set of test values ​​of mineral composition parameters; i Let i be the rock volume value corresponding to the i-th test value of the mineral composition parameter; 1≤i≤N, where N is the total number of test values ​​of the mineral composition parameter.

10. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 1, characterized in that, The determination of whether the calculated values ​​of rock physical property parameters completely match the wireline logging data of rock physical property parameters includes: The calculated values ​​of rock physical parameters are plotted as theoretical calculation curves, and the wireline logging data of rock physical parameters are plotted as actual logging curves. Determine whether the theoretically calculated curve and the actual logging curve show similar increasing or decreasing trends within the same depth range; When the theoretical calculation curve and the actual logging curve show dissimilar increasing or decreasing trends within the same depth range, the judgment result is that the calculated value of the output rock physical property parameter does not completely match the wireline logging data of the rock physical property parameter. Given that the theoretical calculation curve and the actual logging curve show similar increasing and decreasing trends within the same depth range, determine the degree of matching between the theoretical calculation curve and the actual logging curve within the same depth range; Compare the matching degree and matching degree threshold between theoretically calculated curves and actual logging curves within the same depth range; If the degree of matching between the theoretical calculation curve and the actual logging curve is greater than the matching threshold in a certain depth range, the output will indicate that the calculated value of the rock physical property parameter does not completely match the wireline logging data of the rock physical property parameter. If the matching degree between the theoretical calculation curve and the actual logging curve is less than or equal to the matching degree threshold across the entire depth range, the output is a judgment result indicating that the calculated value of the rock physical property parameter is completely matched with the wireline logging data of the rock physical property parameter.

11. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 10, characterized in that, The determined theoretical calculation curve and the actual logging curve are at the same depth. Does the range exhibit similar trends of increase or decrease, including: Determine the correlation coefficient between theoretically calculated curves and actual logging curves within the same depth range; Compare the correlation coefficient and correlation coefficient threshold between theoretically calculated curves and actual logging curves within the same depth range; If the correlation coefficient between the theoretical calculation curve and the actual logging curve is greater than the correlation coefficient threshold within the same depth range, the output will be a judgment result indicating that the theoretical calculation curve and the actual logging curve show dissimilar increasing or decreasing trends within the same depth range. If the correlation coefficient between the theoretical calculation curve and the actual logging curve is less than or equal to the correlation coefficient threshold within the same depth range, the output will indicate that the theoretical calculation curve and the actual logging curve show similar increasing or decreasing trends within the same depth range.

12. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 10, characterized in that, The degree of matching between theoretical calculation curves and actual logging curves within the same depth range is determined by calculating the root mean square error, mean absolute error, and / or standard deviation.

13. The method for normalizing electrical logging data based on XRD mineral constraints according to claim 1, characterized in that, In cases where the judgment result is an incomplete match, the wireline logging data of rock physical parameters are normalized based on the calculated values ​​of the rock physical parameters, including: Based on the judgment results, the data area where the calculated values ​​of rock physical property parameters do not completely match the wireline logging data of rock physical property parameters is determined; Based on the data region where the calculated values ​​of rock physical parameters do not completely match the wireline logging data of rock physical parameters, the average error between the calculated values ​​of rock physical parameters and the wireline logging values ​​of rock physical parameters is determined. Based on the average error between the calculated values ​​of rock physical parameters and the wireline logging values ​​of rock physical parameters, the wireline logging data of rock physical parameters are normalized.

14. A device for normalizing and processing electrical logging data based on XRD mineral constraints, characterized in that, The normalization processing device includes: The acquisition module is used to acquire test data of mineral composition parameters and cable logging data of rock physical property parameters. The mineral composition parameters include at least the rock mineral composition obtained by X-ray diffraction test. The determination module is used to determine the calculated values ​​of rock physical property parameters based on test data of mineral composition parameters using the volume summation method; The judgment module is used to determine whether the calculated values ​​of rock physical property parameters are completely matched with the wireline logging data of rock physical property parameters; The processing module is used to normalize the cable logging data based on the calculated values ​​of rock physical parameters when the judgment result is not a complete match; and not to normalize the cable logging data based on rock physical parameters when the judgment result is a complete match.

15. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one computer program, which is loaded and executed by one or more of the processors to enable the processors to perform the XRD mineral-constrained electrical logging data normalization processing method as described in any one of claims 1 to 13.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to cause the computer to perform the XRD mineral-constrained electrical logging data normalization processing method according to any one of claims 1 to 13.

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