CN116136609A

CN116136609A - Method and device for determining cloudization parameters, computer equipment and storage medium

Info

Publication number: CN116136609A
Application number: CN202111355250.3A
Authority: CN
Inventors: 刘作强; 钟厚财; 邓勇; 刘振宇; 黄友华; 唐军
Original assignee: China National Petroleum Corp; BGP Inc
Current assignee: China National Petroleum Corp; BGP Inc
Priority date: 2021-11-16
Filing date: 2021-11-16
Publication date: 2023-05-19

Abstract

The application provides a method, a device, equipment and a storage medium for determining a clouding parameter, and belongs to the technical field of oil and gas exploration. The method comprises the following steps: acquiring initial logging data of a sandstone reservoir to be determined, wherein the initial logging data comprise resistivity corresponding to a plurality of depth values of the sandstone reservoir; smoothing the resistivity corresponding to the plurality of depth values to obtain smoothed logging data, wherein the smoothed logging data comprises smoothed resistivity corresponding to the plurality of depth values, and the smoothed resistivity is determined based on the plurality of resistivities corresponding to the preset depth range; determining a formation factor of the sandstone reservoir; and determining the clouding parameters of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the depth values and the formation coefficient. The white Yun Hua rate corresponding to the depth values of the sandstone reservoir is determined through the resistivity and the smooth resistivity corresponding to the depth values, and the influence of the depth values on the clouding rate is considered, so that the accuracy of determining the clouding parameters of the whole sandstone reservoir is improved.

Description

Method and device for determining cloudization parameters, computer equipment and storage medium

Technical Field

The application relates to the technical field of oil and gas exploration, in particular to a method, a device, equipment and a storage medium for determining a clouding parameter.

Background

Currently, fracturing modification is an important technology for improving the productivity of a reservoir, and for sandstone reservoirs, the higher the clouding rate is, the higher the productivity improved by fracturing modification is. Thus, in order to determine the capacity of a sandstone reservoir after fracturing, it is necessary to determine a cloudization parameter that is indicative of the cloudization rate of the sandstone reservoir.

In the related art, determining the clouding parameters of a sandstone reservoir through a coring sample of the sandstone reservoir; analyzing rock components of the coring sample, and determining the percentage content of dolomite in the coring sample to obtain the white Yun Hua rate of the coring sample; and determining the clouding rate as the clouding parameter of the sandstone reservoir.

However, because the clouding rates of the sandstone reservoir corresponding to different depth values may be different, the clouding parameters determined by the method only can represent the clouding parameters of the coring position, and cannot accurately represent the clouding parameters of the whole sandstone reservoir, so that the accuracy of determining the clouding parameters of the whole sandstone reservoir by the method is lower.

Disclosure of Invention

The embodiment of the application provides a method, a device, computer equipment and a storage medium for determining a clouding parameter, which can improve the accuracy of determining the clouding parameter of a whole sandstone reservoir. The technical scheme is as follows:

in one aspect, the present application provides a method for determining a clouding parameter, the method comprising:

acquiring initial logging data of a sandstone reservoir to be determined, wherein the initial logging data comprises resistivity corresponding to a plurality of depth values of the sandstone reservoir;

smoothing the resistivity corresponding to the depth values to obtain smoothed logging data, wherein the smoothed logging data comprises smoothed resistivity corresponding to the depth values, and the smoothed resistivity is determined based on the resistivity corresponding to the preset depth range;

determining a formation factor of the sandstone reservoir;

and determining a clouding parameter of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the depth values and the stratum coefficient, wherein the clouding parameter is used for representing the clouding rate corresponding to the depth values of the sandstone reservoir.

In one possible implementation manner, the smoothing the resistivity corresponding to the plurality of depth values to obtain smoothed logging data includes:

For each depth value, determining a target depth range in which the depth value is located;

determining a plurality of target resistivities corresponding to the target depth range;

and taking the median value of the plurality of target resistivities as the smooth resistivity corresponding to the depth value to obtain the smooth logging data.

In another possible implementation manner, the determining the clouding parameter of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the plurality of depth values and the formation coefficient includes:

for each depth value, determining a difference between a resistivity corresponding to the depth value and a smoothed resistivity;

determining a white Yun Hua rate corresponding to the depth value based on the difference value, the smooth resistivity and the stratum coefficient, and obtaining a white Yun Hua rate corresponding to the depth values;

and taking the clouding rates corresponding to the depth values as the clouding parameters of the sandstone reservoir.

In another possible implementation manner, the determining the white Yun Hua rate corresponding to the depth value based on the difference value, the smoothing resistivity, and the formation coefficient includes:

based on the difference, the smoothed resistivity, and the formation coefficient, determining a white Yun Hua rate corresponding to the depth value by the following equation one;

Equation one:

wherein Dol represents the white Yun Hua rate corresponding to the depth value, A represents the stratum coefficient, RT _smo -RT represents the difference, RT represents the resistivity, RT _smo Representing the smoothed resistivity.

In another possible implementation, the method further includes:

determining a plurality of actual white Yun Hua rates corresponding to coring samples of a plurality of target depth values, and determining a plurality of clouding rates corresponding to the plurality of target depth values from the clouding parameters;

determining a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates;

and under the condition that the correlation coefficient is larger than a preset threshold value, determining that the accuracy of the clouding parameters of the sandstone reservoir meets the standard.

In another possible implementation manner, the determining a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates includes:

determining a first variance of the plurality of clouding rates, a second variance of the plurality of actual clouding rates, and a covariance between the plurality of clouding rates and the plurality of actual clouding rates;

based on the first variance, the second variance, and the covariance, a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates is determined.

In another possible implementation manner, the determining a correlation coefficient between the plurality of actual clouding rates based on the first variance, the second variance, and the covariance includes:

determining correlation coefficients between the plurality of clouding rates and the plurality of actual clouding rates based on the first variance, the second variance, and the covariance by the following formula two;

formula II:

wherein r (Dol) _x ,Dol _y ) Represents the correlation coefficient, cov (Dol _x ,Dol _y ) Representing the covariance, var [ Dol ] _x ]Representing the first variance, var [ Dol ] _y ]Representing the second variance.

In another aspect, the present application provides a device for determining a clouding parameter, where the device includes:

the acquisition module is used for acquiring initial logging data of the sandstone reservoir to be determined, wherein the initial logging data comprise resistivity corresponding to a plurality of depth values of the sandstone reservoir;

the smoothing processing module is used for carrying out smoothing processing on the resistivity corresponding to each depth value to obtain smoothed logging data, wherein the smoothed logging data comprises smoothed resistivity corresponding to the depth values, and the smoothed resistivity is a median value of the resistivities corresponding to the preset depth range;

A first determination module for determining formation coefficients of the sandstone reservoir;

and the second determining module is used for determining the clouding parameters of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the depth values and the stratum coefficient, wherein the clouding parameters are used for representing the clouding rates corresponding to the depth values of the sandstone reservoir.

In a possible implementation manner, the smoothing module is configured to determine, for each depth value, a target depth range in which the depth value is located; determining a plurality of target resistivities corresponding to the target depth range; and taking the median value of the plurality of target resistivities as the smooth resistivity corresponding to the depth value to obtain the smooth logging data.

In another possible implementation manner, the second determining module is configured to determine, for each depth value, a difference between a resistivity corresponding to the depth value and a smoothed resistivity; determining a white Yun Hua rate corresponding to the depth value based on the difference value, the smooth resistivity and the stratum coefficient, and obtaining a white Yun Hua rate corresponding to the depth values; and taking the clouding rates corresponding to the depth values as the clouding parameters of the sandstone reservoir.

In another possible implementation manner, the second determining module is configured to determine, based on the difference value, the smoothed resistivity, and the formation coefficient, a white Yun Hua rate corresponding to the depth value according to the following formula one;

equation one:

In another possible implementation, the apparatus further includes:

a third determining module, configured to determine a plurality of actual white Yun Hua rates corresponding to coring samples of a plurality of target depth values, and determine a plurality of clouding rates corresponding to the plurality of target depth values from the clouding parameters;

a fourth determining module, configured to determine correlation coefficients between the plurality of clouding rates and the plurality of actual clouding rates;

and a fifth determining module, configured to determine that the accuracy of the clouding parameter of the sandstone reservoir meets the standard when the correlation coefficient is greater than a preset threshold.

In another possible implementation manner, the fourth determining module is configured to determine a first variance of the plurality of clouding rates, a second variance of the plurality of actual clouding rates, and a covariance between the plurality of clouding rates and the plurality of actual clouding rates; based on the first variance, the second variance, and the covariance, a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates is determined.

In another possible implementation manner, the fourth determining module is configured to determine a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates based on the first variance, the second variance, and the covariance by a formula two;

formula II:

In another aspect, embodiments of the present application provide a computer device, the computer device comprising: a processor and a memory, the memory having stored therein at least one program code that is loaded and executed by the processor to implement the operations performed in the method for determining a cloudiness parameter as described in any one of the possible implementations.

In another aspect, embodiments of the present application provide a computer readable storage medium having at least one program code stored therein, where the at least one program code is loaded and executed by a processor to implement operations performed in a method for determining a clouding parameter according to any one of the possible implementations described above.

In another aspect, embodiments of the present application provide a computer program product comprising at least one program code loaded and executed by a processor to implement operations performed in a method for determining a clouding parameter as described in any one of the possible implementations.

The beneficial effects of the technical scheme provided by the embodiment of the application at least comprise:

according to the method for determining the clouding parameters, due to the fact that the white Yun Hua rate corresponding to the depth values of the sandstone reservoir can be determined through the resistivity and the smooth resistivity corresponding to the depth values of the sandstone reservoir, the clouding parameters of the sandstone reservoir are represented through the clouding rates corresponding to the depth values, and compared with the clouding parameters of the sandstone reservoir represented only through the clouding parameters of the coring position of a certain position, the accuracy of determining the clouding parameters of the whole sandstone reservoir is improved due to the fact that the influence of the depth values on the clouding rate of the sandstone reservoir is considered.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart illustrating a method of determining a cloudization parameter, according to an exemplary embodiment;

FIG. 2 is a schematic diagram illustrating a deep resistance curve according to an exemplary embodiment;

FIG. 3 is a schematic diagram illustrating a spike jump of a deep resistance curve in accordance with an exemplary embodiment;

FIG. 4 is a schematic diagram illustrating a smoothed resistance curve in accordance with an exemplary embodiment;

FIG. 5 is a flowchart illustrating a method of determining a cloudization parameter, according to an exemplary embodiment;

FIG. 6 is a schematic diagram illustrating one method of determining correlation coefficients according to an exemplary embodiment;

FIG. 7 is a block diagram illustrating a determination device of a cloudization parameter according to an exemplary embodiment;

FIG. 8 is a block diagram illustrating a means for determining a cloudization parameter in accordance with an exemplary embodiment;

fig. 9 is a block diagram of a computer device, according to an example embodiment.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

Fig. 1 is a flowchart illustrating a method for determining a cloudization parameter according to an exemplary embodiment. Referring to fig. 1, the method includes:

101. The method comprises the steps that initial logging data of a sandstone reservoir to be determined are obtained by computer equipment, wherein the initial logging data comprise resistivity corresponding to a plurality of depth values of the sandstone reservoir.

In one possible implementation, the computer device determines initial well logging data for the sandstone reservoir from a correspondence between stored reservoir identifications and well logging data; wherein the well logging data comprises well logging data for the well within the sandstone reservoir, the well logging data comprising resistivity for a plurality of depth values. Correspondingly, the method comprises the following steps: the method comprises the steps that computer equipment determines a target reservoir identification of a sandstone reservoir to be determined; determining target logging information corresponding to the target reservoir identification from the corresponding relation between the stored reservoir identification and the logging information according to the target reservoir identification; and determining the resistivity corresponding to the depth values as initial logging data of the sandstone reservoir.

In one possible implementation, during drilling operations on a sandstone reservoir, a worker measures resistivity of multiple depth values of the sandstone reservoir to obtain log data; the staff upload the logging data to the computer equipment; and the computer equipment stores the logging information and the reservoir identification of the sandstone reservoir where the well is drilled in an associated mode, and a corresponding relation between the reservoir identification and the logging information is obtained. In the embodiment of the present application, the number of the plurality of depth values is not particularly limited, and may be set and changed as needed. In one possible implementation, the operator measures a resistivity every predetermined distance, and the number of depth values is related to the depth of the borehole. Alternatively, the preset distance may be any value between 0.1m and 0.5 m; for example, if the preset distance is 0.125m, one resistivity is measured every 0.125 m.

In one possible implementation, referring to fig. 2, the log is a deep resistivity curve that includes resistivity for a plurality of depth values of the sandstone reservoir. Wherein the abscissa represents the resistivity ranging from 0Ω·m to 1000Ω·m; the ordinate represents depth values ranging from 4960m to 4970m. It should be noted that, after the clouding of the sandstone reservoir, a series of peak jumps may occur in the deep resistance curve, so that the white Yun Hua rate of the sandstone reservoir can be determined based on the deep resistance curve, that is, the deep resistance curve is a sensitive curve related to the clouding of the sandstone reservoir. For example, referring to fig. 3, the deep resistance curves for a and B wells, where there is a spike jump in resistivity for clouded segments and no spike jump in resistivity for non-clouded segments.

In embodiments of the present application, since the initial log data for the sandstone reservoir is determined from the log data that has been drilled, which is the completion within the sandstone reservoir, the actual resistivity of the multiple depth values of the sandstone reservoir can be reflected.

102. And the computer equipment performs smoothing processing on the resistivities corresponding to the depth values to obtain smoothed logging data, wherein the smoothed logging data comprises smoothed resistivities corresponding to the depth values of the sandstone reservoir, and the smoothed resistivities are determined based on the resistivities corresponding to the preset depth range.

In one possible implementation, for each depth value, the depth value is smoothed by a plurality of resistivities corresponding to a plurality of depth values within a preset depth range corresponding to the depth value. The step of determining the preset depth range corresponding to the depth value by the computer equipment is as follows: for each depth value, the computer device determines a difference between the depth value and a preset value as a left end point of the preset depth range, determines a sum of the depth value and the preset value as a right end point of the preset depth range, and determines the preset depth range through the left end point and the right end point. In the embodiment of the present application, the numerical value of the preset value is not particularly limited, and may be set and modified as needed. Alternatively, the preset difference is any value between 0.5m and 5m, for example, 0.5m, 1m, 1.5m, etc.

In one possible implementation, the preset depth range includes a plurality of depth values, and the resistivity corresponding to each depth value is smoothed by a median value of the resistivities corresponding to the plurality of depth values. Correspondingly, the method comprises the following steps: for each depth value, the computer equipment determines a target depth range in which the depth value is located; determining a plurality of target resistivities corresponding to the target depth range; and taking the median value of the plurality of target resistivities as the smooth resistivity corresponding to the depth value to obtain smooth logging data.

Alternatively, referring to FIG. 4, the smoothed log data includes smoothed resistivities for a plurality of depth values of the sandstone reservoir. The peak position of the smoothed log data obtained by smoothing the resistivity corresponding to each depth value is the same as the peak position of the initial log data, that is, the variation trend of the smoothed log data and the initial log data is consistent.

In the embodiment of the application, the resistivity corresponding to each depth value is subjected to smoothing processing, so that the situation that the resistivity in the initial logging data is too high or too low can be avoided, the interference of measurement noise points is reduced, the correlation between the determined smooth logging data and the clouding rate is improved, and the accuracy of the clouding parameters determined based on the smooth logging data is further improved.

103. The computer device determines formation coefficients of the sandstone reservoir.

In the embodiment of the application, the stratum coefficients of the sandstone reservoir corresponding to the same section of sandstone reservoir are basically similar in positions of a plurality of depth values, and can be approximated as a fixed parameter. In one possible implementation, the formation coefficients of a sandstone reservoir are determined from a core sample of the sandstone reservoir. Correspondingly, the computer equipment determines the stratum coefficients of the sandstone reservoir by the following steps: analyzing rock components of a core sample of a sandstone reservoir to obtain the content of dolomite in the core sample, and obtaining the white Yun Hua rate of the core sample; obtaining a depth value of the coring sample, and determining the resistivity corresponding to the depth value and the smooth resistivity corresponding to the depth value; and determining the stratum coefficient of the sandstone reservoir according to the cloudiness rate of the coring sample, the resistivity corresponding to the depth value and the smooth resistivity corresponding to the depth value.

In one possible implementation, the step of determining the formation factor of the sandstone reservoir by the computer device from the cloudiness rate of the coring sample, the resistivity corresponding to the depth value, and the smoothed resistivity corresponding to the depth value is: the computer equipment determines stratum coefficients of the sandstone reservoir according to the cloudiness rate of the coring sample, the resistivity corresponding to the depth value and the smooth resistivity corresponding to the depth value through the following formula III;

and (3) a formula III:

wherein A represents the formation factor of the sandstone reservoir, dol (1) represents the white Yun Hua rate of the coring sample, RT (1) represents the resistivity of the depth value at which the coring sample is located, and RT _smo (1) The smoothed resistivity, which represents the depth value at which the coring sample is located.

In the embodiment of the application, as the stratum coefficients of the sandstone reservoir are similar at the positions of the depth values corresponding to the same sandstone reservoir, the stratum coefficients of the sandstone reservoir can be determined by determining the stratum coefficients of the coring samples of the sandstone reservoir, so that the stratum coefficients of the depth values of the sandstone reservoir do not need to be calculated one by one, and the efficiency of determining the stratum coefficients of the sandstone reservoir is improved.

104. The computer device determines a clouding parameter of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the plurality of depth values and the formation coefficient, the clouding parameter being used to represent the clouding rate corresponding to the plurality of depth values of the sandstone reservoir.

In one possible implementation, this step is: for each depth value, the computer device determines a difference between the resistivity corresponding to the depth value and the smoothed resistivity; determining a white Yun Hua rate corresponding to the depth value based on the difference value, the smooth resistivity and the stratum coefficient, and obtaining white Yun Hua rates corresponding to a plurality of depth values; and taking the clouding rates corresponding to the depth values as the clouding parameters of the sandstone reservoir.

In the embodiment of the application, as the resistivity, the smooth resistivity and the stratum coefficient corresponding to the depth value are parameters related to the clouding rate, the clouding parameters are determined from multiple dimensions by combining the resistivity, the smooth resistivity and the stratum coefficient, so that the accuracy of the determined clouding parameters is improved.

In one possible implementation, the step of determining the cloudiness rate corresponding to the depth value by the computer device based on the difference, the smoothed resistivity, and the formation factor is: the computer equipment determines the white Yun Hua rate corresponding to the depth value through the following formula I based on the difference value, the smooth resistivity and the stratum coefficient;

equation one:

It should be noted that, with continued reference to fig. 4, after the computer device determines the white Yun Hua rate corresponding to each depth value and obtains the white clouding rates corresponding to the plurality of depth values, the white Yun Hua rate curve may also be determined according to the white Yun Hua rates corresponding to the plurality of depth values, as shown in fig. 4; and determining a difference curve according to the differences corresponding to the depth values, as shown in fig. 4.

In an embodiment of the present application, the computer device may further determine whether the accuracy of the clouding parameters of the sandstone reservoir determined through steps 101 to 104 meets the standard according to the actual white Yun Hua rate of the plurality of coring samples selected from the sandstone reservoir. Accordingly, referring to fig. 5, the method further includes the following steps 105 to 107.

105. The computer device determines a plurality of actual white Yun Hua rates for the coring samples for the plurality of target depth values and a plurality of clouding rates for the plurality of target depth values from the clouding parameters.

In one possible implementation, the step of determining, by the computer device, a plurality of actual cloudiness rates corresponding to the coring samples for the plurality of target depth values is: for each coring sample, the computer device analyzes the rock composition of the coring sample, determines the percentage content of dolomite in the coring sample, determines the percentage content as the actual white Yun Hua rate of the coring sample, and obtains a plurality of actual cloudiness rates corresponding to the coring samples with a plurality of target depth values.

In the embodiment of the present application, the number of the plurality of target depth values is not particularly limited, and may be set and modified as needed. The plurality of coring samples for the target depth values may be the same coring sample that has been drilled or may be different coring samples that have been drilled. For example, referring to FIG. 6, the coring samples for the plurality of target depth values are the coring samples for drilled A, drilled B, drilled C, drilled D, and drilled E, respectively. Wherein, the core samples of the well A are 3, the core samples of the well B are 1, the core samples of the well C are 3, the core samples of the well D are 1, and the core samples of the well E are 10. Wherein the abscissa is used to represent the actual white Yun Hua rate of the coring sample for a plurality of target depth values; the ordinate is used to represent the rate of cloudiness determined by the plurality of target depth values.

In one possible implementation, the clouding parameters include a clouding rate corresponding to a plurality of depth values of the sandstone reservoir. Correspondingly, the computer equipment determines a plurality of clouding rates corresponding to the plurality of target depth values from the clouding rates corresponding to the plurality of depth values according to the plurality of target depth values.

106. The computer device determines a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates.

In one possible implementation, this step is: the computer device determining a first variance of the plurality of clouding rates, a second variance of the plurality of actual clouding rates, and a covariance between the plurality of clouding rates and the plurality of actual clouding rates; based on the first variance, the second variance, and the covariance, a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates is determined.

In one possible implementation, the computer device determines a first variance of the plurality of clouding rates from an average of the plurality of clouding rates; accordingly, the computer device determines the first variances of the plurality of cloudiness rates as: the computer device determining a first average of the plurality of clouding rates and a number of the plurality of clouding rates; for each cloudiness rate, determining a difference of the cloudiness rate from a first average; determining a first variance of the plurality of clouding rates according to the difference and the number of the plurality of clouding rates by the following formula four;

Equation four:

wherein Var [ Dol ] _x ]Representing the first variance, dol _i Indicating the i-th rate of clouding,

a first average value of the plurality of clouding rates is represented, and n represents the number of the plurality of clouding rates.

In one possible implementation, the computer device determines a second variance of the plurality of actual clouding rates from an average of the plurality of actual clouding rates; accordingly, the computer device determines the second variances of the plurality of actual clouding rates as: the computer device determining a second average of the plurality of actual clouding rates and a number of the plurality of actual clouding rates; for each actual white Yun Hua rate, determining a difference of the actual white cloud rate from the second average; determining a second variance of the plurality of actual clouding rates according to the difference and the number of the plurality of actual clouding rates by the following formula five;

formula five:

wherein Var [ Dol ] _y ]Representing the second variance, dol _j Representing the actual white Yun Hua rate of the jth coring sample,

and a second average value representing a plurality of actual clouding rates, m representing the number of the plurality of actual clouding rates.

In one possible implementation, the step of determining the correlation coefficient between the plurality of actual clouding rates by the computer device based on the first variance, the second variance, and the covariance is: the computer device determines correlation coefficients between the plurality of clouding rates and the plurality of actual clouding rates based on the first variance, the second variance, and the covariance by the following formula two;

Formula II:

wherein r (Dol) _x ,Dol _y ) Representing the correlation coefficient, cov (Dol) _x ,Dol _y ) Representing covariance, var[Dol _x ]Representing the first variance, var [ Dol ] _y ]Representing a second variance.

For example, with continued reference to FIG. 6, the core samples for well A are 3, the core samples for well B are 1, the core samples for well C are 3, the core samples for well D are 1, and the core samples for well E are 10. The computer device determines a correlation coefficient between the plurality of rates of cloudiness and the plurality of actual rates of cloudiness as 0.9782.

107. And under the condition that the correlation coefficient is larger than a preset threshold value, the computer equipment determines that the accuracy of the clouding parameters of the sandstone reservoir meets the standard.

In the embodiment of the present application, the value of the preset threshold is not particularly limited, and may be set and modified as required. Optionally, the data of the preset threshold is any value between 0.8 and 1, for example, the preset threshold is 0.85. With continued reference to fig. 6, if the computer device determines that the correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates is 0.9782, which is greater than the preset threshold value of 0.85, the computer device determines that the accuracy of the clouding parameters of the sandstone reservoir meets the standard.

In a possible implementation manner, if the correlation coefficient is not greater than the preset threshold, the computer device determines that the accuracy of the clouding parameter of the sandstone reservoir does not reach the standard, and changes the clouding parameter of the sandstone reservoir to other drilled logging data, and determines the clouding parameter of the sandstone reservoir through steps 101 to 103 until the correlation coefficient is greater than the preset threshold.

In the embodiment of the application, the accuracy of the obtained clouding parameters of the sandstone reservoir is verified through the correlation coefficients of the actual clouding rates corresponding to the coring samples with the target depth values and the calculated clouding rates, so that the accuracy of the obtained clouding parameters is ensured to be larger than a preset threshold value, and the accuracy of the determined clouding parameters is improved.

It should be noted that the computer device may also determine the dessert reservoir according to a plurality of cloudiness rates corresponding to a plurality of depth values. Correspondingly, the method comprises the following steps: the computer device determines a maximum Bai Yunhua rate from the plurality of clouding rates, determines a depth value corresponding to the maximum clouding rate, and uses a reservoir corresponding to the depth value as a premium reservoir, i.e., a dessert reservoir.

Fig. 7 is a block diagram illustrating a device for determining a cloudization parameter according to an exemplary embodiment. Referring to fig. 7, the apparatus includes:

an obtaining module 701, configured to obtain initial logging data of a sandstone reservoir to be determined, where the initial logging data includes resistivity corresponding to a plurality of depth values of the sandstone reservoir;

the smoothing module 702 is configured to perform smoothing processing on the resistivity corresponding to the depth value for each depth value to obtain smoothed logging data, where the smoothed logging data includes smoothed resistivities corresponding to a plurality of depth values, and the smoothed resistivity is a median value of the resistivities corresponding to a preset depth range;

A first determining module 703 for determining a formation factor of the sandstone reservoir;

the second determining module 704 is configured to determine a clouding parameter of the sandstone reservoir based on the resistivity and the smoothed resistivity corresponding to the plurality of depth values and the formation coefficient, where the clouding parameter is used to represent a clouding rate corresponding to the plurality of depth values of the sandstone reservoir.

In one possible implementation, the smoothing module 702 is configured to determine, for each depth value, a target depth range in which the depth value is located; determining a plurality of target resistivities corresponding to the target depth range; and taking the median value of the plurality of target resistivities as the smooth resistivity corresponding to the depth value to obtain smooth logging data.

In another possible implementation, the second determining module 704 is configured to determine, for each depth value, a difference between a resistivity corresponding to the depth value and the smoothed resistivity; determining a white Yun Hua rate corresponding to the depth value based on the difference value, the smooth resistivity and the stratum coefficient, and obtaining white Yun Hua rates corresponding to a plurality of depth values; and taking the clouding rates corresponding to the depth values as the clouding parameters of the sandstone reservoir.

In another possible implementation, the second determining module 704 is configured to determine, based on the difference, the smoothed resistivity, and the formation coefficient, a white Yun Hua rate corresponding to the depth value according to the following formula one;

Equation one:

In another possible implementation, referring to fig. 8, the apparatus further includes:

a third determining module 705, configured to determine a plurality of actual white Yun Hua rates corresponding to the coring samples with a plurality of target depth values, and determine a plurality of clouding rates corresponding to the plurality of target depth values from the clouding parameters;

a fourth determining module 706, configured to determine correlation coefficients between the plurality of clouding rates and the plurality of actual clouding rates;

and a fifth determining module 707, configured to determine that the accuracy of the clouding parameter of the sandstone reservoir meets the standard if the correlation coefficient is greater than a preset threshold.

In another possible implementation, the fourth determining module 706 is configured to determine a first variance of the plurality of clouding rates, a second variance of the plurality of actual clouding rates, and a covariance between the plurality of clouding rates and the plurality of actual clouding rates; based on the first variance, the second variance, and the covariance, a correlation coefficient between the plurality of clouding rates and the plurality of actual clouding rates is determined.

In another possible implementation manner, the fourth determining module 706 is configured to determine, based on the first variance, the second variance, and the covariance, a correlation coefficient between the plurality of cloudiness rates and the plurality of actual cloudiness rates through the following formula two;

Formula II:

wherein r (Dol) _x ,Dol _y ) Representing the correlation coefficient, cov (Dol) _x ,Dol _y ) Representing covariance, var [ Dol ] _x ]Representing the first variance, var [ Dol ] _y ]Representing a second variance.

The embodiment of the application provides a determination device for a clouding parameter, because the white Yun Hua rate corresponding to a plurality of depth values of a sandstone reservoir can be determined through the resistivity and the smooth resistivity corresponding to the plurality of depth values of the sandstone reservoir, and then the clouding parameter of the sandstone reservoir is represented through the clouding rate corresponding to the plurality of depth values.

Fig. 9 shows a block diagram of a computer device 900 provided by an exemplary embodiment of the invention. The computer device 900 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion picture expert compression standard audio plane 3), an MP4 (Moving Picture Experts Group Audio Layer IV, motion picture expert compression standard audio plane 4) player, a notebook computer, or a desktop computer. Computer device 900 may also be referred to by other names as user device, portable computer device, laptop computer device, desktop computer device, etc.

In general, the computer device 900 includes: a processor 901 and a memory 902.

Processor 901 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 901 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 901 may also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also referred to as a CPU (Central Processing Unit ); a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 901 may integrate a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content required to be displayed by the display screen. In some embodiments, the processor 901 may also include an AI (Artificial Intelligence ) processor for processing computing operations related to machine learning.

The memory 902 may include one or more computer-readable storage media, which may be non-transitory. The memory 902 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 902 is used to store at least one instruction for execution by processor 901 to implement the method of determining a cloudiness parameter provided by a method embodiment in the present application.

In some embodiments, the computer device 900 may also optionally include: a peripheral interface 903, and at least one peripheral. The processor 901, memory 902, and peripheral interface 903 may be connected by a bus or signal line. The individual peripheral devices may be connected to the peripheral device interface 903 via buses, signal lines, or circuit boards. Specifically, the peripheral device includes: at least one of radio frequency circuitry 904, a display 905, a camera 906, audio circuitry 907, positioning components 908, and a power source 909.

The peripheral interface 903 may be used to connect at least one peripheral device associated with an I/O (Input/Output) to the processor 901 and the memory 902. In some embodiments, the processor 901, memory 902, and peripheral interface 903 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 901, the memory 902, and the peripheral interface 903 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.

The Radio Frequency circuit 904 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 904 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 904 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 904 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuitry 904 may communicate with other computer devices via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuit 904 may also include NFC (Near Field Communication ) related circuits, which are not limited in this application.

The display 905 is used to display a UI (user interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 905 is a touch display, the display 905 also has the ability to capture touch signals at or above the surface of the display 905. The touch signal may be input as a control signal to the processor 901 for processing. At this time, the display 905 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 905 may be one, providing a front panel of the computer device 900; in other embodiments, the display 905 may be at least two, respectively disposed on different surfaces of the computer device 900 or in a folded design; in still other embodiments, the display 905 may be a flexible display disposed on a curved surface or a folded surface of the computer device 900. Even more, the display 905 may be arranged in an irregular pattern other than rectangular, i.e., a shaped screen. The display 905 may be made of LCD (Liquid Crystal Display ), OLED (Organic Light-Emitting Diode) or other materials.

The camera assembly 906 is used to capture images or video. Optionally, the camera assembly 906 includes a front camera and a rear camera. Typically, the front camera is disposed on a front panel of the computer device and the rear camera is disposed on a rear surface of the computer device. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, camera assembly 906 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.

The audio circuit 907 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 901 for processing, or inputting the electric signals to the radio frequency circuit 904 for voice communication. For purposes of stereo acquisition or noise reduction, the microphone may be multiple, each disposed at a different location of the computer device 900. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 901 or the radio frequency circuit 904 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, the audio circuit 907 may also include a headphone jack.

The location component 908 is used to locate the current geographic location of the computer device 900 to enable navigation or LBS (Location Based Service, location-based services). The positioning component 908 may be a positioning component based on the United states GPS (Global Positioning System ), the Beidou system of China, the Granati system of Russia, or the Galileo system of the European Union.

The power supply 909 is used to power the various components in the computer device 900. The power supply 909 may be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 909 includes a rechargeable battery, the rechargeable battery can support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, computer device 900 also includes one or more sensors 910. The one or more sensors 910 include, but are not limited to: acceleration sensor 911, gyroscope sensor 912, pressure sensor 913, fingerprint sensor 914, optical sensor 915, and proximity sensor 916.

The acceleration sensor 911 can detect the magnitudes of accelerations on three coordinate axes of the coordinate system established by the computer device 900. For example, the acceleration sensor 911 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 901 may control the display 905 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal acquired by the acceleration sensor 911. The acceleration sensor 911 may also be used for the acquisition of motion data of a game or a user.

The gyro sensor 912 may detect a body direction and a rotation angle of the computer device 900, and the gyro sensor 912 may collect a 3D motion of the user on the computer device 900 in cooperation with the acceleration sensor 911. The processor 901 may implement the following functions according to the data collected by the gyro sensor 912: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.

The pressure sensor 913 may be disposed on a side frame of the computer device 900 and/or on an underside of the display 905. When the pressure sensor 913 is disposed on the side frame of the computer device 900, a holding signal of the computer device 900 by the user may be detected, and the processor 901 performs left-right hand recognition or quick operation according to the holding signal collected by the pressure sensor 913. When the pressure sensor 913 is provided at the lower layer of the display 905, the processor 901 performs control of the operability control on the UI interface according to the pressure operation of the user on the display 905. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

The fingerprint sensor 914 is used for collecting the fingerprint of the user, and the processor 901 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 914, or the fingerprint sensor 914 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the processor 901 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 914 may be provided on the front, back, or side of the computer device 900. When a physical key or vendor Logo is provided on the computer device 900, the fingerprint sensor 914 may be integrated with the physical key or vendor Logo.

The optical sensor 915 is used to collect the intensity of ambient light. In one embodiment, the processor 901 may control the display brightness of the display panel 905 based on the intensity of ambient light collected by the optical sensor 915. Specifically, when the ambient light intensity is high, the display luminance of the display screen 905 is turned up; when the ambient light intensity is low, the display luminance of the display panel 905 is turned down. In another embodiment, the processor 901 may also dynamically adjust the shooting parameters of the camera assembly 906 based on the ambient light intensity collected by the optical sensor 915.

A proximity sensor 916, also referred to as a distance sensor, is typically provided on the front panel of the computer device 900. Proximity sensor 916 is used to capture the distance between the user and the front of computer device 900. In one embodiment, when the proximity sensor 916 detects that the distance between the user and the front of the computer device 900 gradually decreases, the processor 901 controls the display 905 to switch from the bright screen state to the off screen state; when the proximity sensor 916 detects that the distance between the user and the front surface of the computer device 900 gradually increases, the display 905 is controlled by the processor 901 to switch from the off-screen state to the on-screen state.

Those skilled in the art will appreciate that the architecture shown in fig. 9 is not limiting of the computer device 900, and may include more or fewer components than shown, or may combine certain components, or employ a different arrangement of components.

The embodiment of the application also provides a computer readable storage medium, wherein at least one program code is stored in the computer readable storage medium, and the at least one program code is loaded and executed by a processor to realize the method for determining the cloudization parameters in any one of the possible implementation manners.

The embodiment of the application also provides a computer program product, which comprises at least one program code, and the at least one program code is loaded and executed by a processor to realize the method for determining the clouding parameters in any one of the possible implementation manners.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

The foregoing description of the preferred embodiments is merely exemplary in nature and is in no way intended to limit the invention, since it is intended that all modifications, equivalents, improvements, etc. that fall within the spirit and scope of the invention.

Claims

1. A method for determining a cloudization parameter, the method comprising:

determining a formation factor of the sandstone reservoir;

2. The method of claim 1, wherein smoothing the resistivity for the plurality of depth values to obtain smoothed log data comprises:

3. The method of claim 1, wherein the determining the clouding parameters of the sandstone reservoir based on the resistivity and smoothed resistivity for the plurality of depth values and the formation coefficients comprises:

4. The method of claim 3, wherein the determining a white Yun Hua rate for the depth value based on the difference, the smoothed resistivity, and the formation factor comprises:

equation one:

5. The method according to claim 1, wherein the method further comprises:

6. The method of claim 5, wherein said determining a correlation coefficient between said plurality of rates of cloudiness and said plurality of actual rates of cloudiness comprises:

7. The method of claim 6, wherein the determining a correlation coefficient between the plurality of actual clouding rates based on the first variance, the second variance, and the covariance comprises:

formula II:

wherein r (Dol) _x ，Dol _y ) Represents the correlation coefficient, cov (Dol _x ，Dol _y ) Representing the covariance, var [ Dol ] _x ]Representing the first variance, var [ Dol ] _y ]Representing the second variance.

8. A device for determining a cloudization parameter, the device comprising:

9. A computer device, the computer device comprising:

a processor and a memory having stored therein at least one program code loaded and executed by the processor to carry out the operations performed in the method of determining a cloudiness parameter as claimed in any one of claims 1 to 7.

10. A computer readable storage medium having stored therein at least one program code loaded and executed by a processor to implement the operations performed in the method of determining a cloudiness parameter as claimed in any one of claims 1 to 7.