CN111812744A

CN111812744A - Stratum compressibility determining method and device and computer storage medium

Info

Publication number: CN111812744A
Application number: CN201910288211.2A
Authority: CN
Inventors: 李忠诚; 王志文; 宋鹏; 孙文铁; 肖丽佳; 周萍; 张慧宇; 周俊廷; 李金池
Original assignee: Petrochina Co Ltd
Current assignee: Petrochina Co Ltd
Priority date: 2019-04-11
Filing date: 2019-04-11
Publication date: 2020-10-23
Anticipated expiration: 2039-04-11
Also published as: CN111812744B

Abstract

The application discloses a method and a device for determining formation compressibility and a computer storage medium, and belongs to the technical field of oil and gas field development. According to the method, the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the relationship between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir are determined according to the full wave train logging data of each well in the N wells, the brittleness index of the non-reservoir in the first well is determined according to the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer, and the brittleness index of each type of reservoir in at least one type of reservoir in the first well is determined according to the relationship between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir. The determined brittleness index of the non-reservoir and the brittleness index of the reservoir are more accurate, the accuracy of determining the brittleness index of the stratum in the first well is improved, and correspondingly, the accuracy of determining the compressibility of the stratum in the first well is improved.

Description

Stratum compressibility determining method and device and computer storage medium

Technical Field

The application relates to the technical field of oil and gas field development, in particular to a method and a device for determining formation compressibility and a computer storage medium.

Background

Currently, in the process of oil production, it is often necessary to fracture the formation. It is often desirable to determine the compressibility of a formation prior to fracturing the formation. The compressibility of the formation depends on the brittleness of the rock in the formation. Brittleness of rock in the formation refers to the ease with which rock in the formation can be broken. The brittleness of rock in the formation is often expressed by a formation brittleness index. Wherein determining formation compressibility is also a determination of the formation brittleness index.

In the related art, when determining the brittleness index of a formation, full-wave-train logging data for well a in a well in a study area where full-wave-train logging has been performed is generally selected. And determining the transverse wave time difference of the well A in all the stratums and the longitudinal wave time difference of the well A in all the stratums according to the full wave train logging data of the well A. And selecting a stable marker layer in the well A, and determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the transverse wave time difference of the well A in all the stratums and the longitudinal wave time difference of the well A in all the stratums. By stable marker layer is meant that the formations in all wells in the investigation region contain one type of formation, which may be, for example, a mudstone layer.

And for a well B in the research area except for full wave train logging, acquiring acoustic logging data of the well B, wherein the acoustic logging data comprises longitudinal wave time differences corresponding to different depths in the well B. And determining the transverse wave time difference corresponding to the well B at different depths according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the longitudinal wave time difference corresponding to the well B at different depths. And determining the formation brittleness index of the well B according to the longitudinal wave time difference corresponding to different depths in the well B and the transverse wave time difference corresponding to different depths of the well B. Wherein, all stratum include reservoir and non-reservoir, and the mudstone belongs to non-reservoir. The transverse wave time difference and the longitudinal wave time difference are used for representing the speed of sound wave in rock propagation in the stratum. Because the density of different rocks in the stratum is different, the propagation speed of sound waves in different rocks in the stratum is different, and the brittleness of the rocks is influenced by the density of the rocks, so that the stratum brittleness index can be determined according to the longitudinal wave time difference and the transverse wave time difference.

The formation brittleness index of the well B is determined according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the related technology. The lithology of different types of formations in the formation may be different, and therefore, the formation brittleness index of well B, determined from the relationship between the shear wave moveout and the longitudinal wave moveout of the stable marker layer, may not be suitable for all types of formations in well B. That is, the accuracy of the formation brittleness index determined in the related art is low, so that the accuracy of the finally determined formation compressibility is also low.

Content of application

The embodiment of the application provides a formation compressibility determination method, a formation compressibility determination device and a computer storage medium, which can improve the accuracy of determining formation compressibility. The technical scheme is as follows:

in a first aspect, a formation compressibility determination method is provided, the method comprising:

determining a relation between a transverse wave time difference and a longitudinal wave time difference of a stable marker layer and a relation between a transverse wave time difference and a longitudinal wave time difference of each type of reservoir layer in at least one type of reservoir layer according to full wave train logging data of each well in N wells for performing full wave train logging in a research area, wherein the full wave train logging data is used for representing propagation time difference of sound waves at different depths of a stratum, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir layer;

determining the brittleness index of a non-reservoir stratum in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well, wherein the first well is any well except for a well in the research area for full wave train logging;

and determining the brittleness index of each type of reservoir in the at least one type of reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data is used for indicating the longitudinal wave time difference corresponding to the acoustic waves at different depths of the stratum.

Optionally, the determining, according to full-wave train logging data of each of N wells in the study area in which full-wave train logging is performed, a relationship between a transverse wave time difference and a longitudinal wave time difference of the stable marker layer includes:

determining longitudinal wave time difference of a stable marker layer in each well in the N wells and transverse wave time difference of the stable marker layer in each well according to the full wave train logging data of each well in the N wells;

and determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each well of the N wells and the transverse wave time difference of the stable marker layer in each well.

Optionally, the determining, according to the full-wave train logging data of each of the N wells performing full-wave train logging in the research area, a relationship between a shear wave moveout and a compressional wave moveout of each of at least one type of reservoir includes:

for a first type of reservoir in the at least one type of reservoir, determining a compressional wave time difference of the first type of reservoir in each well of the N wells and a shear wave time difference of the first type of reservoir in each well according to full wave train logging data of each well of the N wells, wherein the first type of reservoir is any one of the at least one type of reservoir;

and determining the relation between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir according to the longitudinal wave time difference of the first type of reservoir in each well of the N wells and the shear wave time difference of the first type of reservoir in each well.

Optionally, the determining the brittleness index of the non-reservoir stratum in the first well according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer and the acoustic logging data of the first well comprises:

obtaining density log data for the first well, the density log data being indicative of rock densities at different depths of a formation;

determining a plurality of dynamic Young's moduli and a plurality of dynamic Poisson ratios of a non-reservoir stratum in the first well according to the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer, the acoustic logging data of the first well and the density logging data of the first well, wherein the dynamic Young's moduli refer to Young's moduli obtained by a dynamic method, the Young's moduli are used for indicating the supporting capacity of the fractured rock, the dynamic Poisson ratios refer to Poisson ratios obtained by the dynamic method, the Poisson ratios are used for indicating the fracturing capacity of the rock under stress, the dynamic Young's moduli correspond to the dynamic Poisson ratios one to one, and each dynamic Young's modulus and the corresponding dynamic Poisson ratio correspond to one formation depth;

determining a static Young modulus according to each dynamic Young modulus in the plurality of dynamic Young moduli to obtain a plurality of static Young moduli;

determining a static Poisson ratio according to each dynamic Poisson ratio in the dynamic Poisson ratios to obtain a plurality of static Poisson ratios, wherein the static Young modulus is the Young modulus obtained by a static method, the static Poisson ratio is the Poisson ratio obtained by the static method, the static Young moduli correspond to the static Poisson ratios one by one, and each static Young modulus corresponds to a stratum depth;

and determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson ratio.

Optionally, the determining the brittleness index of each of the at least one type of reservoir in the first well according to the relationship between the shear wave moveout and the compressional wave moveout of each of the at least one type of reservoir and the sonic logging data of the first well comprises:

obtaining density logging data of the first well;

for a first type of reservoir in the at least one type of reservoir, determining a plurality of dynamic Young's moduli and a plurality of dynamic Poisson's ratios of the first type of reservoir according to the relation between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir, the acoustic logging data of the first well and the density logging data of the first well, wherein the plurality of dynamic Young's moduli correspond to the plurality of dynamic Poisson's ratios one to one, and each dynamic Young's modulus corresponds to one formation depth with the corresponding dynamic Poisson's ratio;

determining a static Poisson ratio according to each dynamic Poisson ratio in the plurality of dynamic Poisson ratios to obtain a plurality of static Poisson ratios, wherein the plurality of static Young moduli correspond to the plurality of static Poisson ratios one by one, and each static Young modulus corresponds to a stratum depth with the corresponding static Poisson ratio;

In a second aspect, there is provided a formation compressibility determination apparatus, the apparatus comprising:

the system comprises a first determination module, a second determination module and a third determination module, wherein the first determination module is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of a stable marker layer and the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to the full wave train logging data of each of N wells for performing full wave train logging in a research area, the full wave train logging data is used for representing the propagation time difference of sound waves at different depths of a stratum, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir;

a second determining module, configured to determine a brittleness index of a non-reservoir stratum in the first well according to a relationship between a transverse wave time difference and a longitudinal wave time difference of the stable marker layer and the acoustic logging data of the first well, where the first well is any well other than a well in the research area in which full-wave-train logging is performed;

and the third determining module is used for determining the brittleness index of each type of reservoir in the at least one type of reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data is used for indicating the longitudinal wave time difference corresponding to different depths.

Optionally, the first determining module includes:

the first determination unit is used for determining the longitudinal wave time difference of the stable marker layer in each well in the N wells and the transverse wave time difference of the stable marker layer in each well according to the full wave train logging data of each well in the N wells;

and the second determining unit is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer according to the longitudinal wave time difference of the stable mark layer in each well in the N wells and the transverse wave time difference of the stable mark layer in each well.

Optionally, the first determining module further includes:

a third determining unit, configured to determine, for a first type of reservoir in the at least one type of reservoir, a compressional wave time difference of the first type of reservoir in each well of the N wells and a shear wave time difference of the first type of reservoir in each well according to full wavetrain logging data of each well of the N wells, where the first type of reservoir is any one of the at least one type of reservoir;

and the fourth determining unit is used for determining the relation between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir according to the longitudinal wave time difference of the first type of reservoir in each well of the N wells and the shear wave time difference of the first type of reservoir in each well.

Optionally, the second determining module includes:

a first obtaining unit for obtaining density log data of the first well, the density log data being indicative of rock densities at different depths in a formation;

a fifth determining unit, configured to determine, according to a relationship between a transverse wave time difference and a longitudinal wave time difference of the stable marker layer, acoustic logging data of the first well, and density logging data of the first well, a plurality of dynamic young moduli and a plurality of dynamic poisson ratios of a non-reservoir layer in the first well, where the dynamic young moduli are young moduli obtained by a dynamic method, the young moduli are used to indicate a supporting capability of a rock after fracture, the dynamic poisson ratios are poisson ratios obtained by the dynamic method, the poisson ratios are used to indicate a fracture capability of the rock under stress, the plurality of dynamic young moduli correspond to the plurality of dynamic poisson ratios one to one, and each dynamic young modulus and corresponding dynamic poisson ratio correspond to one formation depth;

a sixth determining unit, configured to determine a static young's modulus according to each of the plurality of dynamic young's moduli, to obtain a plurality of static young's moduli;

a seventh determining unit, configured to determine a static poisson ratio according to each of the multiple dynamic poisson ratios to obtain multiple static poisson ratios, where the static young's modulus is a young's modulus obtained through a static method, the static poisson ratio is a poisson ratio obtained through a static method, the multiple static young's moduli correspond to the multiple static poisson ratios one to one, and each static young's modulus and corresponding static poisson ratio correspond to a formation depth;

and the eighth determining unit is used for determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson ratio.

Optionally, the third determining module includes:

the second acquisition unit is used for acquiring density logging data of the first well;

a ninth determining unit, configured to determine, for a first type of reservoir in the at least one type of reservoir, a plurality of dynamic young moduli and a plurality of dynamic poisson ratios of the first type of reservoir according to a relationship between a shear wave moveout and a longitudinal wave moveout of the first type of reservoir, acoustic logging data of the first well, and density logging data of the first well, where the plurality of dynamic young moduli correspond to the plurality of dynamic poisson ratios one to one, and each dynamic young modulus and corresponding dynamic poisson ratio correspond to one formation depth;

a tenth determining unit, configured to determine a static young's modulus according to each dynamic young's modulus in the plurality of dynamic young's moduli, so as to obtain a plurality of static young's moduli;

an eleventh determining unit, configured to determine a static poisson ratio according to each of the multiple dynamic poisson ratios, to obtain multiple static poisson ratios, where the multiple static young moduli correspond to the multiple static poisson ratios one to one, and each static young modulus corresponds to a formation depth corresponding to the corresponding static poisson ratio;

and the twelfth determining unit is used for determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson's ratio.

In a third aspect, a formation compressibility determination apparatus, the apparatus comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the steps of any of the methods of the first aspect described above.

In a fourth aspect, a computer-readable storage medium has stored thereon instructions which, when executed by a processor, implement the steps of any of the methods of the first aspect described above.

In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the steps of any of the methods of the first aspect described above.

The technical scheme provided by the embodiment of the application has the following beneficial effects:

according to the method, the stratum of each of N wells for full-wave train logging in a research area is divided into a reservoir and a non-reservoir, and the relation between the transverse wave time difference and the longitudinal wave time difference of a stable marker layer and the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir are determined according to full-wave train logging data of each of the N wells. And determining the brittleness index of the non-reservoir stratum in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well. And determining the brittleness index of each type of reservoir in the at least one type of reservoir in the first well according to the relation between the shear wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well. That is, in the present application, when determining the brittleness index of the formation in the first well, the brittleness index of the non-reservoir is determined according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer, and the brittleness index of the reservoir is determined according to the relationship between the shear wave time difference and the longitudinal wave time difference of the reservoir. The determined brittleness index of the non-reservoir and the brittleness index of the reservoir are more accurate, the accuracy of determining the brittleness index of the stratum in the first well is improved, and correspondingly, the accuracy of determining the compressibility of the stratum in the first well is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a flow chart of a formation compressibility determination method provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of data fitting between longitudinal wave time difference of a stable marker layer and transverse wave time difference of the stable marker layer according to an embodiment of the present application;

FIG. 3 is a schematic diagram of data fitting between longitudinal wave time difference of a gas layer and transverse wave time difference of the gas layer according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of data fitting between longitudinal wave time difference of a dry layer and transverse wave time difference of the dry layer according to an embodiment of the present disclosure;

FIG. 5 is a graphical illustration of a data fit of the dynamic Young's modulus of a stable marker layer provided in an embodiment of the present application to a laboratory measured static Young's modulus;

FIG. 6 is a schematic diagram of data fitting of the dynamic Poisson's ratio of a stable marker layer to a laboratory-determined static Poisson's ratio provided in an embodiment of the present application;

FIG. 7 is a schematic illustration of a log and different formations provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of a formation compressibility determination apparatus provided by an embodiment of the present application;

fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

Before explaining the formation compressibility determination method provided by the present application, an application scenario of the formation compressibility determination method provided by the present application is briefly introduced. Formations can be generally divided into reservoirs and non-reservoirs by the porosity of the formation. Generally, when the porosity of a formation is greater than a numerical threshold, the formation may be classified as a reservoir, and when the porosity of a formation is equal to or less than the numerical threshold, the formation may be classified as a non-reservoir, and the porosity of a formation refers to a ratio of a volume of pores in rock in the formation to a total volume of rock. Meanwhile, the reservoir may be classified as an oil reservoir or a gas reservoir according to the substance stored in the reservoir. In the gas storage layer, the gas storage layer can be divided into a gas layer, a differential gas layer and a dry layer according to different gas saturation degrees of the gas storage layer. The gas layer means that the saturation degree of gas contained in the gas storage layer is greater than a saturation threshold value, the gas layer is poor in the gas layer means that the saturation degree of gas contained in the gas storage layer is smaller than the saturation threshold value, and the gas layer is dry in the gas layer, and the saturation degree of gas contained in the gas storage layer is 0. Wherein, the gas saturation refers to the ratio of the volume of gas in the gas storage layer to the volume of pores in the gas storage layer.

Prior to fracturing a well in a zone of interest, the compressibility of the reservoir in the well needs to be determined, and sonic logging data is typically used in determining the compressibility of the reservoir in the well, i.e., determining the brittleness index of the reservoir in the well. Because the acoustic logging data is used for indicating the time difference of longitudinal waves corresponding to different depths in the well, when the brittleness index of the reservoir is determined by using the acoustic logging data, the determined brittleness index of the reservoir also indicates the brittleness index corresponding to different depths in the well.

Fig. 1 is a flowchart of a formation compressibility determination method provided in an embodiment of the present application, and as shown in fig. 1, the method includes the following steps:

step 101: determining the relation between the transverse wave time difference and longitudinal wave time difference of a stable mark layer and the relation between the transverse wave time difference and longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to the full wave train logging data of each of N wells for performing full wave train logging in a research area, wherein the full wave train logging data is used for representing the propagation time difference of sound waves at different depths of the stratum, N is a positive integer greater than or equal to 1, and the stable mark layer is a non-reservoir.

Because the stable marker layer is a non-reservoir, the lithology of the non-reservoir is usually different from that of the reservoir, so that when the formation brittleness index is determined, the formation needs to be divided into the reservoir and the non-reservoir, and the brittleness index of the reservoir and the brittleness index of the non-reservoir are respectively determined. And the brittleness index of the reservoir is related to the relation between the transverse wave and the longitudinal wave in the acoustic wave time difference of the reservoir, and the brittleness index of the non-reservoir is related to the relation between the transverse wave and the longitudinal wave in the acoustic wave time difference of the non-reservoir, so that the relation between the transverse wave time difference and the longitudinal wave time difference in the acoustic wave time difference of the reservoir and the relation between the transverse wave time difference and the longitudinal wave time difference in the acoustic wave time difference of the stable mark layer are respectively determined.

(1) And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer.

In a possible implementation manner, determining a relationship between a transverse wave time difference and a longitudinal wave time difference of the stable marker layer according to full-wave train logging data of each of N wells in the study area in which full-wave train logging is performed may specifically be: and determining the longitudinal wave time difference of the stable marker layer in each well in the N wells and the transverse wave time difference of the stable marker layer in each well according to the full wave train logging data of each well in the N wells. And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each well of the N wells and the transverse wave time difference of the stable marker layer in each well.

When the full-wave-train logging is performed on each well in the N wells, the obtained full-wave-train logging data of each well comprises the transverse wave time difference of each well in all the stratums and the longitudinal wave time difference of each well in all the stratums, so that the full-wave-train logging data of each well can be separated, and the longitudinal wave time difference of the stable mark layer in each well and the transverse wave time difference of the stable mark layer in each well can be separated. And then determining the longitudinal wave time difference of the stable marker layer in each well and the transverse wave time difference of the stable marker layer in each well according to the full wave train logging data of each well.

In a possible implementation manner, determining a relationship between a shear wave time difference and a longitudinal wave time difference of the stable marker layer according to a longitudinal wave time difference of the stable marker layer in each well and a shear wave time difference of the stable marker layer in each well may specifically be: and constructing a first longitudinal wave time difference set by the longitudinal wave time difference of the stable mark layer in each well, constructing a first transverse wave time difference set by the transverse wave time difference of the stable mark layer in each well, performing data fitting according to the first longitudinal wave time difference set and the first transverse wave time difference set, and taking the result after the data fitting as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer. The data fitting can be performed by taking the longitudinal wave time difference as a horizontal coordinate and the transverse wave time difference as a vertical coordinate.

For example, full-wave-train logging is performed on 3 wells in the study area, resulting in full-wave-train logging data for each of the 3 wells. And determining the transverse wave time difference of the stable mark layer in each well and the longitudinal wave time difference of the stable mark layer in each well according to the full wave train logging data of each well. And constructing a first transverse wave time difference set by the transverse wave time difference of the stable mark layer in each well, and constructing a first longitudinal wave time difference set by the longitudinal wave time difference of the stable mark layer in each well. As shown in fig. 2, using the longitudinal wave time difference as the abscissa and the transverse wave time difference as the ordinate, performing data fitting on all transverse wave time differences in the first transverse wave time difference set and all longitudinal wave time differences in the second longitudinal wave time difference set to obtain the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer as follows:

y＝1.2527x+105.57

in the above formula, y represents a transverse wave time difference, and x represents a longitudinal wave time difference. R²Indicating the fitting accuracy. Generally, the transverse wave time difference is Δ t_sDenotes the difference in longitudinal wave time by Δ t_pThus, the above formula may also be:

Δt_s＝1.2527Δt_p+105.57

optionally, in another possible implementation manner, determining, according to the compressional wave time difference of the stable marker layer in each well and the shear wave time difference of the stable marker layer in each well, the relationship between the shear wave time difference and the compressional wave time difference of the stable marker layer may specifically be further: and for any well C in each well, performing data fitting on the transverse wave time difference of the stable marker layer in the well C and the longitudinal wave time difference of the stable marker layer in the well C, and taking the result of the data fitting as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well C. For other wells except for the well C in each well, the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in other wells can be determined according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well C. After determining the relationship between the shear wave moveout and the longitudinal wave moveout for the stable marker layer in each well, the relationship between the shear wave moveout and the longitudinal wave moveout for the stable marker layer in each well is compared. And if the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in each well is close, taking the relation between the transverse wave time difference and the longitudinal wave time difference of any well in each well as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer. And if the relation difference between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in each well is obvious, selecting any one of the similar fitting results in the same type from the fitting results of the transverse wave time difference and the longitudinal wave time difference data of the stable mark layer in each well, and taking the fitting result as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in each well.

The fact that the relation between the transverse wave time difference and the longitudinal wave time difference is similar means that every two adjacent fitting results in the fitting results are the same type of fitting result. The obvious difference of the relationship between the transverse wave time difference and the longitudinal wave time difference means that the fitting results are of different types, or the difference between coefficients corresponding to the same parameters in a plurality of functions of the same type used for representing the fitting results is greater than a numerical threshold. The same type of fitting result means that the fitted functions are the same type of functions. A close fit means that the difference between coefficients of the same parameter in the plurality of functions used to represent the fit is less than a numerical threshold. For example, y 2x +3 and y 2.01x +3 are the same type of function, and the coefficients of parameter x are 2 and 2.01, respectively, and the difference 0.01 between 2 and 2.01 is smaller than the numerical threshold 0.1, then y 2x +3 and y 2.01x +3 are similar fitting results.

For example, 3 wells in the study area for performing full-wave-train logging are respectively a well X, a well Y and a well Z, and the transverse wave time difference of the stable marker layer in the well X and the longitudinal wave time difference of the stable marker layer in the well X, the transverse wave time difference of the stable marker layer in the well Y and the longitudinal wave time difference of the stable marker layer in the well Z are respectively determined according to the full-wave-train logging data of the well X, the full-wave-train logging data of the well Y and the full-wave-train logging data of the well Z. Determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well X as the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well Y, the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well Z respectively₁＝a₁x+b₁The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Y is Y₂＝a₂x+b₂The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Z is y₃＝a₃x+b₃。

Since the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well X, the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Y, and the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Z are linear functions, a is compared with a₁、a₂And a₃，b₁、b₂And b₃. If a is₁、a₂And a₃A difference therebetween is smaller than a first preset threshold, and b₁、b₂And b₃The difference value between the y values is less than a second preset threshold value, y is determined₁＝a₁x+b₁、y₂＝a₂x+b₂And y₃＝a₃x+b₃Any one of which serves as a relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer. If a is₁、a₂And a₃The difference between them is greater than a first predetermined threshold value, b₁、b₂And b₃The difference value between the two is greater than a second preset threshold value, a is obtained₁、a₂And a₃The average of these three values being taken as the coefficient of the parameter x, b₁、b₂And b₃The average of these three values is taken as a constant in the relationship between the transverse wave moveout and the longitudinal wave moveout of the stable marker layer.

If the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well X is y₁＝a₁x²+b₁The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Y is Y₂＝a₂x+b₂The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well Z is y₃＝a₃x+b₃Then compare a₂And a₃，b₂And b₃. If a is₂And a₃The difference between them is less than a first predetermined threshold value, b₂And b₃The difference between y and y is less than a second preset threshold value₂＝a₂x+b₂And y₃＝a₃x+b₃Any one of which serves as a relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer. If a is₂And a₃The difference between them is greater than a first preset threshold value, b₂And b₃The difference value between the two is greater than a second preset threshold value, a is determined₂And a₃The average of these two values being taken as the coefficient of the parameter x, b₂And b₃The average value of the two values is used as the time difference and longitudinal wave time of transverse wave and longitudinal wave of the stable mark layerA constant in the relationship between the differences.

(2) And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the reservoir.

In a possible implementation manner, determining, according to full-wavetrain logging data of each of N wells in a study area, a relationship between a transverse wave time difference and a longitudinal wave time difference of each reservoir in at least one type of reservoir may specifically be: for a first type of reservoir in the at least one type of reservoir, determining compressional wave time differences of the first type of reservoir in each of the N wells and shear wave time differences of the first type of reservoir in each of the N wells according to full wave train log data for each of the N wells. And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the first type of reservoir in each well of the N wells according to the longitudinal wave time difference of the first type of reservoir in each well and the transverse wave time difference of the first type of reservoir in each well. Wherein the first type of reservoir is any one of at least one type of reservoir.

Because there are different types of reservoirs in each well, in order to ensure that the finally determined compressibility of each type of reservoir in the at least one type of reservoir is accurate, the relationship between the shear wave moveout and the compressional wave moveout of each type of reservoir in the at least one type of reservoir needs to be determined.

When the full-wave-train logging is performed on each well in the N wells, the obtained full-wave-train logging data of each well comprises the transverse wave time difference of each well in all the stratums and the longitudinal wave time difference of each well in all the stratums, so that the transverse wave time difference of a first type of reservoir in at least one type of reservoir in each well and the longitudinal wave time difference of the first type of reservoir in each well can be determined according to the full-wave-train logging data of each well. Typically, after obtaining the full-wavetrain log data for each well, the full-wavetrain log data for each well is separated to isolate the compressional moveout for the first type of reservoir and the shear moveout for the first type of reservoir in each well. And for each longitudinal wave time difference of at least one type of reservoir in each well and the transverse wave time difference of each type of reservoir, determining according to the longitudinal wave time difference of the first type of reservoir and the transverse wave time difference of the first type of reservoir.

In addition, in a possible implementation manner, determining, according to the compressional wave moveout of the first type reservoir in each of the N wells and the shear wave moveout of the first type reservoir in each of the N wells, a relationship between the shear wave moveout and the compressional wave moveout of the first type reservoir may specifically be: and constructing a second longitudinal wave time difference set by longitudinal wave time differences of the first type of reservoirs in each well, constructing a second transverse wave time difference set by transverse wave time differences of the first type of reservoirs in each well, performing data fitting according to the second longitudinal wave time difference set and the second transverse wave time difference set, and taking a result after the data fitting as a relation between the transverse wave time differences and the longitudinal wave time differences of the first type of reservoirs. The data fitting can be performed by taking the longitudinal wave time difference as a horizontal coordinate and the transverse wave time difference as a vertical coordinate.

For example, full-wave-train logging is performed on 3 wells in the study area, resulting in full-wave-train logging data for each of the 3 wells. And determining the transverse wave time difference of the first type of reservoir in each well and the longitudinal wave time difference of the first type of reservoir in each well according to the full wave train logging data of each well. And constructing a second shear wave time difference set by using the shear wave time differences of the first type of reservoirs in each well, and constructing a second compressional wave time difference set by using the compressional wave time differences of the first type of reservoirs in each well. As shown in fig. 3, when the first type of reservoir is a gas reservoir, the longitudinal wave moveout is taken as the abscissa, the transverse wave moveout is taken as the ordinate, and data fitting is performed on all transverse wave moveouts in the second transverse wave moveout set and all longitudinal wave moveouts in the second longitudinal wave moveout set, so as to obtain the following relationship between the transverse wave moveout and the longitudinal wave moveout of the gas reservoir:

y＝1.4661x+44.55

Δt_s＝1.4661Δt_p+44.55

when the first type of reservoir is a dry layer, as shown in fig. 4, data fitting is performed on all the transverse wave time differences in the second transverse wave time difference set and all the longitudinal wave time differences in the second longitudinal wave time difference set by using longitudinal wave time differences as a horizontal coordinate and transverse wave time differences as a vertical coordinate, and the relationship between the transverse wave time differences and the longitudinal wave time differences of the dry layer is obtained as follows:

y＝1.6345x+14.861

Δt_s＝1.6345Δt_p+14.861

optionally, in another possible implementation manner, the implementation manner of determining the relationship between the shear wave time difference and the longitudinal wave time difference of the first type reservoir in each of the N wells according to the longitudinal wave time difference of the first type reservoir in each of the N wells and the shear wave time difference of the first type reservoir in each of the N wells may refer to another possible implementation manner of determining the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each well and the shear wave time difference of the stable marker layer in each well, which is not described herein again.

Step 102: and determining the brittleness index of a non-reservoir stratum in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well, wherein the first well is any well except the well in the research area for carrying out full wave train logging.

In a possible implementation manner, step 102 may specifically be: density log data for the first well is obtained. And determining a plurality of dynamic Young moduli and a plurality of dynamic Poisson ratios of the non-reservoir layer in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer, the acoustic logging data of the first well and the density logging data of the first well. Determining a static Young's modulus according to each dynamic Young's modulus in the plurality of dynamic Young's moduli to obtain a plurality of static Young's moduli. And determining a static Poisson ratio according to each dynamic Poisson ratio in the plurality of dynamic Poisson ratios to obtain a plurality of static Poisson ratios. And determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson ratio.

Wherein the density log data is indicative of rock densities at different depths in the formation. The dynamic young modulus refers to young modulus obtained by a dynamic method, and the young modulus is used for indicating the supporting capacity of the rock after cracking. The dynamic poisson ratio is the poisson ratio obtained by a dynamic method, and is used for indicating the fracture capacity of the rock under stress. The plurality of dynamic Young's moduli correspond to the plurality of dynamic Poisson ratios one to one, and each dynamic Young's modulus and the corresponding dynamic Poisson ratio correspond to one formation depth. The static Young modulus is the Young modulus obtained by a static method, the static Poisson ratio is the Poisson ratio obtained by the static method, the plurality of static Young moduli correspond to the plurality of static Poisson ratios one by one, and each static Young modulus and the corresponding static Poisson ratio correspond to one stratum depth. In addition, the dynamic method is to determine the young modulus of the rock by testing the propagation time difference of the sound wave in the rock, the static method is to apply a constant tensile stress or compressive stress on the rock, and the young modulus of the rock is determined according to the applied tensile stress and the strain of the rock under the tensile stress, or the young modulus of the rock is determined according to the applied compressive stress and the strain of the rock under the compressive stress.

Wherein the density log data for the first well may be pre-stored.

In addition, determining a plurality of dynamic young moduli and a plurality of dynamic poisson ratios of a non-reservoir in the first well according to the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer, the acoustic logging data of the first well, and the density logging data of the first well can be realized according to the following formula:

in the above formula, YME_{Movable part}Expressing dynamic Young's modulus, PR_{Movable part}Representing the dynamic Poisson's ratio, p representing the density of the rock, Δ t_sRepresenting the difference in transverse wave time, Δ t_pThe longitudinal wave time difference is indicated.

In addition, the determining a static young's modulus according to each dynamic young's modulus in the plurality of dynamic young's moduli may be implemented in a manner of: the laboratory measured static young's modulus is obtained for each of the M depths in the stable marker layer. The dynamic young's modulus corresponding to each of the M depths is found from a plurality of dynamic young's moduli. And fitting data of the dynamic Young modulus corresponding to each depth in the M depths and the static Young modulus measured in a laboratory corresponding to each depth in the N depths, and taking the result of the data fitting as the relation between the static Young modulus and the dynamic Young modulus. Determining a static Young's modulus based on each of the plurality of dynamic Young's moduli and a relationship between the static Young's modulus and the dynamic Young's modulus. The static young's modulus measured in a laboratory is plotted on the abscissa and the dynamic young's modulus is plotted on the ordinate.

For example, the static young's moduli measured in the laboratory corresponding to 13 mutually different depths in the stable marker layer are acquired, the dynamic young's modulus corresponding to each of the 13 mutually different depths is found from the plurality of dynamic young's moduli, and the 13 dynamic young's moduli and the static young's moduli measured in the laboratory are subjected to data fitting. As shown in fig. 5, the static young's modulus is plotted on the abscissa and the dynamic young's modulus is plotted on the ordinate, and the data fitting results are obtained by fitting the data of 13 dynamic young's moduli and the static young's moduli measured in 13 laboratories. As shown in the following formula:

y＝0.7x+0.772

in the above formula, y represents the static Young's modulus, x represents the dynamic Young's modulus, R²Indicating the fitting accuracy. YME for dynamic Young's modulus in general_{Movable part}Static Young's modulus is expressed by YME_QuietThus, the above equation can be expressed again as:

YME_quiet＝0.7YME_{Movable part}+0.772

After obtaining the relationship between the static young's modulus and the dynamic young's modulus, the plurality of static young's moduli may be obtained by substituting each of the plurality of dynamic young's moduli into the relationship between the static young's modulus and the dynamic young's modulus.

In addition, determining a static poisson ratio according to each of the plurality of dynamic poisson ratios may be implemented in a manner that: obtaining a laboratory-determined static Poisson's ratio for each of the N depths in the stable marker layer. And searching a dynamic Poisson ratio corresponding to each depth in the N depths from a plurality of dynamic Poisson ratios. And performing data fitting on the dynamic Poisson ratio corresponding to each depth in the N depths and the static Poisson ratio determined by a laboratory corresponding to each depth in the N depths, and taking the result of the data fitting as the relation between the static Poisson ratio and the dynamic Poisson ratio. A static poisson's ratio is determined based on each of the plurality of dynamic poisson's ratios and a relationship between the static poisson's ratio and the dynamic poisson's ratio. Wherein, the static Poisson's ratio measured in a laboratory is used as an abscissa, and the dynamic Poisson's ratio is used as an ordinate.

For example, laboratory-measured static poisson ratios corresponding to 13 mutually different depths in the stable marker layer are obtained, a dynamic poisson ratio corresponding to each depth at the 13 mutually different depths is searched from a plurality of dynamic poisson ratios, and data fitting is performed on the 13 dynamic poisson ratios and the 13 laboratory-measured static poisson ratios. As shown in fig. 6, the static poisson ratios measured in 13 laboratories and the 13 dynamic poisson ratios were subjected to data fitting with the static poisson ratios as abscissa and the dynamic poisson ratios as ordinate, and the result of the data fitting was taken as the relationship between the static poisson ratios and the dynamic poisson ratios. As shown in the following formula

y＝1.263x-0.047

In the above formula, y represents a static Poisson's ratio, x represents a dynamic Poisson's ratio, R²Indicating the fitting accuracy. In general, PR is used for dynamic Poisson's ratio_{Movable part}Indicating that the static Poisson's ratio is PR_QuietThus, the above equation can be expressed again as:

PR_quiet＝1.263PR_{Movable part}-0.047

After the relationship between the static poisson ratio and the dynamic poisson ratio is obtained, each dynamic poisson ratio in the dynamic poisson ratios can be substituted into the relationship between the static poisson ratio and the dynamic poisson ratio to obtain the static poisson ratios.

In addition, in a possible implementation manner, the determining the formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson's ratio may specifically be: maximum and minimum values of a plurality of dynamic young's moduli of non-reservoirs in the first well are obtained. Maximum and minimum values of a plurality of dynamic Poisson's ratios of non-reservoirs in the first well are obtained. Determining a first normalized Young's modulus of the non-reservoir in the first well according to a first static Young's modulus of the non-reservoir in the first well, a maximum value and a minimum value of the plurality of dynamic Young's moduli, the first static Young's modulus being any one of the plurality of static Young's moduli of the non-reservoir in the first well. Determining a first normalized plurality of poisson ratios of the non-reservoir in the first well according to a first static poisson ratio of the non-reservoir in the first well, a maximum value and a minimum value of the dynamic poisson ratios, wherein the first static poisson ratio is any one of the plurality of static poisson ratios of the non-reservoir in the first well. A first brittleness index of the non-reservoir in the first well is determined based on the first normalized young's modulus of the non-reservoir in the first well and the first normalized poisson's ratio of the non-reservoir in the first well. For each static young's modulus of the plurality of static young's moduli of the non-reservoir and the corresponding static poisson's ratio, the formation brittleness index at the corresponding formation depth may be determined in the manner described above.

Wherein determining the first normalized plurality of Young's moduli of the non-reservoir in the first well based on the first static Young's modulus of the non-reservoir in the first well, the maximum and minimum of the plurality of dynamic Young's moduli may be implemented according to:

in the above formula, YME_britDenotes the normalized Young's modulus, YME_QuietRepresenting the static Young's modulus, YME_maxRepresents the maximum value of a plurality of dynamic Young's moduli, YME_minRepresents the minimum of the plurality of dynamic young's moduli.

Additionally, determining a first normalized poisson ratio of the non-reservoir in the first well based on the first static poisson ratio of the non-reservoir in the first well, the maximum and minimum of the dynamic poisson ratios may be achieved according to the following equation:

in the above formula, PR_britDenotes the normalized Poisson's ratio, PR_QuietRepresenting the static Poisson ratio, PR_maxRepresenting the maximum value, PR, of a plurality of dynamic Poisson ratios_minRepresenting the minimum of a plurality of dynamic poisson ratios.

Additionally, determining a first brittleness index of the non-reservoir in the first well based on the first normalized young's modulus of the non-reservoir in the first well and the first normalized poisson's ratio of the non-reservoir in the first well may be accomplished according to the following equation:

BRIT＝(YME_brit+PR_brit)/2

in the above formula, BRIT represents brittleness index, YME_britDenotes the normalized Young's modulus, PR_britRepresenting the normalized poisson ratio.

Step 103: and determining the brittleness index of each type of reservoir in the at least one type of reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data of the first well is used for indicating the longitudinal wave time difference corresponding to different depths in the first well.

In a possible implementation manner, step 103 may specifically be: density log data for the first well is obtained. And for a first type of reservoir in the at least one type of reservoir, determining a plurality of dynamic Young's moduli and a plurality of dynamic Poisson's ratios of the first type of reservoir according to the relation between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir, the acoustic logging data of the first well and the density logging data of the first well. Determining a static Young's modulus according to each dynamic Young's modulus in the plurality of dynamic Young's moduli to obtain a plurality of static Young's moduli. And determining a static Poisson ratio according to each dynamic Poisson ratio in the plurality of dynamic Poisson ratios to obtain a plurality of static Poisson ratios. And determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson ratio.

According to the relationship between the shear wave time difference and the longitudinal wave time difference of the first reservoir, the acoustic logging data of the first well and the density logging data of the first well, the implementation modes of the plurality of dynamic Young's moduli and the plurality of dynamic Poisson's ratios of the first reservoir can be determined by referring to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer and the density logging data of the first well, and the implementation modes of the plurality of dynamic Young's moduli and the plurality of dynamic Poisson's ratios of the non-reservoir in the first well are not described herein again.

In addition, the implementation manner of determining one static young modulus according to each dynamic young modulus in the plurality of dynamic young moduli to obtain the plurality of static young moduli may refer to the implementation manner of determining one static young modulus according to each dynamic young modulus in the plurality of dynamic young moduli in step 102 to obtain the plurality of static young moduli, which is not described herein again.

In addition, the implementation manner of determining one static poisson ratio according to each of the multiple dynamic poisson ratios to obtain the multiple static poisson ratios may refer to the implementation manner of determining one static poisson ratio according to each of the multiple dynamic poisson ratios in step 102 to obtain the multiple static poisson ratios, which is not described herein again.

In addition, the implementation manner for determining the formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio may refer to the implementation manner for determining the formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio in step 102, and is not described herein again.

In order to verify the formation compressibility determination method provided by the embodiment of the present application, a specific verification is performed by the following example.

FIG. 7 is a schematic illustration of a log and different formations provided by embodiments of the present application. As shown in fig. 7, CAL represents a caliper log. GR represents the natural gamma log. RLA1 represents a shallow lateral resistivity log. RLA5 represents a deep lateral resistivity log. CNL represents a neutron porosity log. DEN is the density log. AC represents a sonic log. The Young's modulus before optimization means dynamic Young's modulus. The optimized young's modulus represents the static young's modulus. The pre-optimized poisson's ratio represents a dynamic poisson's ratio. The optimized poisson ratio represents a static poisson ratio. The experimentally determined brittleness index represents the brittleness index determined in the laboratory. The brittleness index before optimization represents the brittleness index determined in the related art. The optimized brittleness index represents the brittleness index determined according to the method of the present application. Comprehensive interpretation refers to the determination of reservoir type from multiple logs. As shown in fig. 7, the lithology section is from top to bottom, the first formation is mudstone. The second formation is pozzolanic mudstone. The third formation is a breccid mudstone. The fourth formation is a breccite. The fifth formation is tuff. The sixth formation is pozzolanic mudstone. The seventh formation is a breccid mudstone. The eighth formation is a breccid tuff mudstone. The ninth formation is breccid mudstone. The tenth formation is a breccid tuff mudstone. The eleventh formation is pozzolanic mudstone. Wherein in fig. 7 different strata are represented by different graphs. In this column, the blocks of the figure have a plurality of lines representing dry layers and only one line represents a poor gas layer, as shown in fig. 7. That is, in interpreting this column in general, the first reservoir from top to bottom is the poor gas zone and the second reservoir is the dry zone. In fig. 7, at A, B, C and D, the left line represents the brittleness index of the reservoir determined in the related art, and the right line represents the brittleness index of the reservoir determined according to the method of the present application. As can be seen from fig. 7, the brittleness index of the reservoir determined according to the method of the present application matches the brittleness index determined in the laboratory more highly, and thus, the brittleness index determined according to the method of the present application has higher accuracy.

It should be noted that, usually, a triaxial fracturing experiment or a uniaxial fracturing experiment is performed on a core in a well in a laboratory to determine the young's modulus and the poisson's ratio of the core, and when the triaxial fracturing experiment or the uniaxial fracturing experiment is performed, a stress with the same magnitude as the formation pressure received in the core is applied around the core to simulate the actual stress of the core in the formation. Thus, the laboratory measured young's modulus and poisson's ratio of the core are relatively accurate. The static brittleness index determined from the young's modulus and poisson's ratio of the core measured in the laboratory is also relatively accurate. The brittleness index of the reservoir determined by the method provided by the application is high in goodness of fit with the brittleness index determined by a laboratory, and the brittleness index of the reservoir determined by the method provided by the application is accurate.

In addition, typically not all formations in a well are cored, and therefore brittleness indices cannot be measured in a laboratory for all depths in the well.

Fig. 8 is a schematic structural diagram of a formation compressibility determining apparatus according to an embodiment of the present application, and as shown in fig. 8, an apparatus 800 includes:

a first determining module 801, configured to determine, according to full-wave train logging data of each of N wells in a study area, a relationship between a transverse wave time difference and a longitudinal wave time difference of a stable marker layer, and a relationship between a transverse wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir, where the full-wave train logging data is used to represent propagation time differences of sound waves at different depths of a formation, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir;

a second determining module 802, configured to determine a brittleness index of a non-reservoir in a first well according to a relationship between a transverse wave time difference and a longitudinal wave time difference of a stable marker layer and acoustic logging data of the first well, where the first well is any well other than a well in a research area in which full-wave train logging is performed;

the third determining module 803 is configured to determine the brittleness index of each type of reservoir in the at least one type of reservoir in the first well according to the relationship between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, where the acoustic logging data of the first well is used to indicate the longitudinal wave time difference corresponding to different depths in the first well.

Optionally, the first determining module 801 includes:

and the second determining unit is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer according to the longitudinal wave time difference of the stable mark layer in each of the N wells and the transverse wave time difference of the stable mark layer in each well.

Optionally, the first determining module 801 further includes:

the third determining unit is used for determining the longitudinal wave time difference of the first type of reservoir in each well of the N wells and the transverse wave time difference of the first type of reservoir in each well according to the full wave train logging data of each well of the N wells for the first type of reservoir in the at least one type of reservoir, wherein the first type of reservoir is any one of the at least one type of reservoir;

and the fourth determining unit is used for determining the relation between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir in each of the N wells according to the longitudinal wave time difference of the first type of reservoir in each of the N wells and the shear wave time difference of the first type of reservoir in each well.

Optionally, the second determining module 802 includes:

the first acquisition unit is used for acquiring density logging data of a first well, and the density logging data are used for indicating rock densities at different depths of a stratum;

a fifth determining unit, configured to determine, according to a relationship between a transverse wave time difference and a longitudinal wave time difference of the stable marker layer, acoustic logging data of the first well, and density logging data of the first well, a plurality of dynamic young moduli and a plurality of dynamic poisson ratios of a non-reservoir layer in the first well, where a dynamic young modulus is a young modulus obtained by a dynamic method, a young modulus is used to indicate a supporting capability of a rock after fracture, a dynamic poisson ratio is a poisson ratio obtained by a dynamic method, a poisson ratio is used to indicate a fracture capability of the rock under a stress action, the plurality of dynamic young moduli correspond to the plurality of dynamic poisson ratios one to one, and each dynamic young modulus and the corresponding dynamic poisson ratio correspond to one formation depth;

a seventh determining unit, configured to determine a static poisson ratio according to each of the multiple dynamic poisson ratios to obtain multiple static poisson ratios, where a static young's modulus refers to a young's modulus obtained by a static method, a static poisson ratio refers to a poisson ratio obtained by a static method, the multiple static young's moduli correspond to the multiple static poisson ratios one to one, and each static young's modulus corresponds to a formation depth;

Optionally, the third determining module 803 includes:

a ninth determining unit, configured to determine, for a first type of reservoir in the at least one type of reservoir, a plurality of dynamic young moduli and a plurality of dynamic poisson ratios of the first type of reservoir according to a relationship between a shear wave time difference and a longitudinal wave time difference of the first type of reservoir, acoustic logging data of the first well, and density logging data of the first well, where the plurality of dynamic young moduli correspond to the plurality of dynamic poisson ratios one to one, and each dynamic young modulus corresponds to one formation depth with respect to the corresponding dynamic poisson ratio;

an eleventh determining unit, configured to determine a static poisson ratio according to each of the multiple dynamic poisson ratios to obtain multiple static poisson ratios, where the multiple static young moduli correspond to the multiple static poisson ratios one to one, and each static young modulus corresponds to a formation depth;

and the twelfth determining unit is used for determining the formation brittleness index at the corresponding formation depth according to each static Young modulus and the corresponding static Poisson ratio.

It should be noted that: the formation compressibility determining apparatus provided in the above embodiment is only illustrated by dividing the above function modules when determining formation compressibility, and in practical applications, the function distribution may be completed by different function modules according to needs, that is, the internal structure of the apparatus is divided into different function modules to complete all or part of the above described functions. In addition, the formation compressibility determining apparatus provided in the above embodiments and the formation compressibility determining method embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.

Fig. 9 shows a block diagram of a terminal 900 according to an exemplary embodiment of the present application. The terminal 900 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer iv, motion video Experts compression standard Audio Layer 4), a notebook computer, or a desktop computer. Terminal 900 may also be referred to by other names such as user equipment, portable terminals, laptop terminals, desktop terminals, and the like.

In general, terminal 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 so forth. The processor 901 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 901 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 901 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 901 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

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 formation compressibility determination methods provided by method embodiments herein.

In some embodiments, terminal 900 can 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 buses or signal lines. Various peripheral devices may be connected to the peripheral interface 903 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 904, a touch display screen 905, a camera assembly 906, an audio circuit 907, a positioning assembly 908, and a power supply 909.

The peripheral interface 903 may be used to connect at least one peripheral related to 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, any one or two of the processor 901, the memory 902 and the peripheral interface 903 may be implemented on a separate chip or circuit board, which is not limited by this embodiment.

The Radio Frequency circuit 904 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 904 communicates with communication networks and other communication devices via electromagnetic signals. The radio frequency circuit 904 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 904 comprises: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuit 904 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation 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 screen 905 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 905 is a touch display screen, the display screen 905 also has the ability to capture touch signals on or over the surface of the display screen 905. The touch signal may be input to the processor 901 as a control signal for processing. At this point, 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 the front panel of the terminal 900; in other embodiments, the number of the display panels 905 may be at least two, and each of the display panels is disposed on a different surface of the terminal 900 or is in a foldable design; in still other embodiments, the display 905 may be a flexible display disposed on a curved surface or a folded surface of the terminal 900. Even more, the display screen 905 may be arranged in a non-rectangular irregular figure, i.e. a shaped screen. The Display panel 905 can be made of LCD (liquid crystal Display), OLED (Organic Light-Emitting Diode), and the like.

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

Audio circuit 907 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user 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 realizing voice communication. For stereo sound acquisition or noise reduction purposes, the microphones may be multiple and disposed at different locations of the terminal 900. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 901 or the radio frequency circuit 904 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, audio circuit 907 may also include a headphone jack.

The positioning component 908 is used to locate the current geographic location of the terminal 900 to implement navigation or LBS (location based Service). The positioning component 908 may be a positioning component based on the GPS (global positioning System) of the united states, the beidou System of china, the graves System of russia, or the galileo System of the european union.

Power supply 909 is used to provide power to the various components in terminal 900. The power source 909 may be alternating current, direct current, disposable or rechargeable. When power source 909 comprises a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

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

The acceleration sensor 911 can detect the magnitude of acceleration in three coordinate axes of the coordinate system established with the terminal 900. For example, the acceleration sensor 911 may be used to detect the components of the gravitational acceleration in three coordinate axes. The processor 901 can control the touch display 905 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 911. The acceleration sensor 911 may also be used for 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 terminal 900, and the gyro sensor 912 may cooperate with the acceleration sensor 911 to acquire a 3D motion of the user on the terminal 900. The processor 901 can implement the following functions according to the data collected by the gyro sensor 912: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.

Pressure sensors 913 may be disposed on the side bezel of terminal 900 and/or underneath touch display 905. When the pressure sensor 913 is disposed on the side frame of the terminal 900, the user's holding signal of the terminal 900 may be detected, and the processor 901 performs left-right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 913. When the pressure sensor 913 is disposed at a lower layer of the touch display 905, the processor 901 controls the operability control on the UI interface according to the pressure operation of the user on the touch display 905. The operability control comprises 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 a fingerprint of the user, and the processor 901 identifies the user according to the fingerprint collected by the fingerprint sensor 914, or the fingerprint sensor 914 identifies the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, processor 901 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings, etc. The fingerprint sensor 914 may be disposed on the front, back, or side of the terminal 900. When a physical key or vendor Logo is provided on the terminal 900, the fingerprint sensor 914 may be integrated with the physical key or vendor Logo.

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

Proximity sensor 916, also known as a distance sensor, is typically disposed on the front panel of terminal 900. The proximity sensor 916 is used to collect the distance between the user and the front face of the terminal 900. In one embodiment, when the proximity sensor 916 detects that the distance between the user and the front face of the terminal 900 gradually decreases, the processor 901 controls the touch display 905 to switch from the bright screen state to the dark screen state; when the proximity sensor 916 detects that the distance between the user and the front surface of the terminal 900 gradually becomes larger, the processor 901 controls the touch display 905 to switch from the breath screen state to the bright screen state.

Those skilled in the art will appreciate that the configuration shown in fig. 9 does not constitute a limitation of terminal 900, and may include more or fewer components than those shown, or may combine certain components, or may employ a different arrangement of components.

Embodiments of the present application also provide a non-transitory computer-readable storage medium, where instructions in the storage medium, when executed by a processor of a terminal, enable the terminal to perform the formation compressibility determination method provided in the embodiment shown in fig. 1.

Embodiments of the present application also provide a computer program product containing instructions that, when executed on a computer, cause the computer to perform the formation compressibility determination method provided by the embodiment shown in fig. 1 above.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

In summary, the present application is only a preferred embodiment and is not intended to be limited by the scope of the present application, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A formation compressibility determination method, the method comprising:

2. The method of claim 1, wherein determining the relationship between the shear wave moveout and the compressional wave moveout for the stable marker layer from the full wavetrain log data for each of the N wells in the study area in which full wavetrain logs were conducted comprises:

3. The method of claim 1, wherein determining the relationship between the shear moveout and the compressional moveout for each of the at least one type of reservoir based on the full wavetrain log data for each of the N wells in the study area in which the full wavetrain log was conducted comprises:

4. The method of claim 1, wherein determining the brittleness index of the non-reservoir in the first well based on the relationship between the shear wave moveout and the compressional wave moveout of the stable marker layer and the sonic logging data for the first well comprises:

5. The method of claim 1, wherein determining the brittleness index of each of the at least one type of reservoir in the first well based on the relationship between the shear moveout and the compressional moveout for each of the at least one type of reservoir, and the sonic logging data for the first well comprises:

obtaining density logging data of the first well;

6. A formation compressibility determination apparatus, the apparatus comprising:

7. The apparatus of claim 6, wherein the first determining module comprises:

8. The apparatus of claim 6, wherein the first determining module further comprises:

9. The apparatus of claim 6, wherein the second determining module comprises:

a first obtaining unit for obtaining density log data of the first well, the density log data being indicative of rock densities at different depths of a formation;

10. The apparatus of claim 6, wherein the third determination module comprises:

11. A formation compressibility determination apparatus, the apparatus comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the steps of any one of the methods of claim 1 to claim 5.

12. A computer readable storage medium having stored thereon instructions which, when executed by a processor, implement the steps of any one of the methods of claims 1 to 5.