CN116413791A

CN116413791A - Method and device for estimating transverse wave speed

Info

Publication number: CN116413791A
Application number: CN202111659968.1A
Authority: CN
Inventors: 徐宝荣; 冉建斌; 于宝利; 王晓辉; 周东言; 戴云捷
Original assignee: China National Petroleum Corp; BGP Inc
Current assignee: China National Petroleum Corp; BGP Inc
Priority date: 2021-12-30
Filing date: 2021-12-30
Publication date: 2023-07-11

Abstract

The embodiment of the application discloses a method and a device for estimating transverse wave speed, and belongs to the technical field of oil and gas exploration. After the rock sample is obtained, the pore width-to-length ratio curve of the pattern sample can be calculated, and then plastic mineral equivalent, brittle mineral equivalent, rock skeleton equivalent, dry rock equivalent, fluid equivalent and fluid replacement are carried out, so that a rock physical model of the rock sample is established, and the transverse wave velocity of the rock sample can be estimated based on the rock physical model. The rock physical model of the rock sample close to the actual shale reservoir is comprehensively built, so that the transverse wave speed estimation of the rock sample is accurate, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well zone selection and increased storage production.

Description

Method and device for estimating transverse wave speed

Technical Field

The embodiment of the application relates to the technical field of oil and gas exploration, in particular to a method and a device for estimating transverse wave speed.

Background

In the technical field of shale oil and gas exploration, the vertical well yield of the shale oil reservoir is low under the influence of the characteristics of the shale oil reservoir, the vertical well yield is mainly increased by virtue of a horizontal well, and the distribution condition of ground stress is a key factor of the fracturing effect of the horizontal well and determines the stability of a fractured well body, the extending direction, the shape and the azimuth of a crack. The pre-stack elastic parameters are used in the calculation of the maximum horizontal main stress and the minimum horizontal main stress, and the accurate transverse wave speed is needed for calculating the high-precision pre-stack elastic parameters.

In the related art, methods for obtaining the transverse wave velocity can be divided into two main categories: the method has the advantages of fast operation, simple operation and good matching effect on the conventional sandstone reservoir operation, but hardly meets the research requirements of complex lithology reservoirs. The other is an equivalent theoretical model method, which needs to obtain various rock physical parameters, and has definite physical meaning although the operation process is complex. The existing shale model has emphasis, and a certain characteristic of shale is highlighted.

Disclosure of Invention

The embodiment of the application provides a method and a device for estimating a transverse wave speed. The technical scheme is as follows:

according to an aspect of the present application, there is provided a method for estimating a shear wave velocity, the method including:

mining a rock sample from a shale reservoir, calculating data required to build a petrophysical model of the rock sample based on a sonic time difference curve, a density curve, and petroelectrical parameters of the rock sample, the required data including a mineral composition curve, a total porosity curve, and a water saturation curve;

calculating a pore width-to-length ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample;

Mixing by utilizing a self-consistent model and a differential equivalent model based on mineral components of the rock sample to respectively obtain plastic mineral equivalent modulus and brittle mineral equivalent modulus of the rock sample;

mixing by utilizing a differential equivalent model based on the plastic mineral equivalent substance and the brittle mineral equivalent substance of the rock sample to obtain the rock skeleton equivalent modulus of the rock sample;

based on the rock skeleton and the porosity of the rock sample, mixing by utilizing a differential equivalent model to obtain the dry rock equivalent modulus of the rock sample;

based on the water saturation of the rock sample, performing fluid mixing by using a Brie index method to obtain the fluid equivalent modulus of the rock sample;

performing fluid replacement by using a Boris fluid replacement model based on the dry rock and the mixed fluid of the rock sample, thereby establishing a petrophysical model of the rock sample;

and estimating the transverse wave velocity of the rock sample based on the petrophysical model.

According to another aspect of the present application, there is provided an apparatus for estimating a shear wave velocity, the apparatus comprising:

a modeling data calculation module for mining a rock sample from a shale reservoir, calculating data required to build a petrophysical model of the rock sample based on a sonic time difference curve, a density curve, and a petroelectrical parameter of the rock sample, the required data including a mineral composition curve, a total porosity curve, and a water saturation curve;

The pore width-to-length ratio calculation module is used for calculating a pore width-to-length ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample;

the rock matrix equivalent module is used for mixing by utilizing a self-consistent model and a differential equivalent model based on mineral components of the rock to respectively obtain plastic mineral equivalent modulus and brittle mineral equivalent modulus of the rock sample;

the rock skeleton equivalent module is used for mixing by utilizing a differential equivalent model based on the plastic mineral equivalent substance and the brittle mineral equivalent substance of the rock sample to obtain the rock skeleton equivalent modulus of the rock sample;

the dry rock equivalent module is used for mixing by utilizing a differential equivalent model based on the rock skeleton and the porosity of the rock sample to obtain the dry rock equivalent modulus of the rock sample;

the fluid equivalent module is used for carrying out fluid mixing by utilizing a Brie index method based on the water saturation of the rock sample to obtain the fluid equivalent modulus of the rock sample;

a fluid replacement module for performing fluid replacement using a Boris fluid replacement model based on the dry rock and the mixed fluid of the rock sample, thereby establishing a petrophysical model of the rock sample;

And the transverse wave speed estimation module is used for estimating the transverse wave speed of the rock sample based on the petrophysical model.

According to another aspect of the present application, there is provided a terminal comprising a processor and a memory having stored therein at least one instruction loaded and executed by the processor to implement a method of estimating shear wave velocity as provided in various aspects of the present application.

According to another aspect of the present application, there is provided a computer readable storage medium having stored therein at least one instruction that is loaded and executed by a processor to implement a method of estimating shear wave velocity as provided by the various aspects of the present application.

According to one aspect of the present application, a computer program product is provided that includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions to cause the computer device to perform the method of estimating shear wave velocity provided in the various alternative implementations described above.

The beneficial effects that technical scheme that this application embodiment provided can include:

after the rock sample is obtained, the pore width-to-length ratio curve of the pattern sample can be calculated, and then plastic mineral equivalent, brittle mineral equivalent, rock skeleton equivalent, dry rock equivalent, fluid equivalent and fluid replacement are carried out, so that a rock physical model of the rock sample is established, and the transverse wave velocity of the rock sample can be estimated based on the rock physical model. The rock physical model of the rock sample close to the actual shale reservoir is comprehensively built, so that the transverse wave speed estimation of the rock sample is accurate, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well zone selection and increased storage production.

Drawings

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

FIG. 1 is a flow chart of a method for estimating shear wave velocity according to an exemplary embodiment of the present application;

FIG. 2 is a flow chart of a method of estimating shear wave velocity provided in accordance with the embodiment of FIG. 1;

FIG. 3 is a flow chart of another method for estimating shear wave velocity provided by an exemplary embodiment of the present application;

FIG. 4 is a graph of the results of a calculation of kerogen (TOC) content using the Passey formula, the multivariate fitting method, the density method, and the natural gamma spectroscopy, respectively, provided herein;

FIG. 5 is a graph of the comparison of results calculated by four methods with measured kerogen (TOC) content provided herein;

FIG. 6 is a graph of the results of a petrophysical modeling correlation curve calculation provided herein;

FIG. 7 is a graph of the intersection of brittle mineral content and measured content as determined by an optimized log interpretation method provided herein;

FIG. 8 is a flow chart of a complex mineral component shale oil petrophysical modeling provided herein;

FIG. 9 is a graph of results of compressional velocity, density, shear velocity using the shale oil petrophysical modeling method of the present application;

FIG. 10 is a graph of the intersection of a shear wave velocity and an observed shear wave velocity obtained using the shale oil petrophysical modeling method of the present application;

FIG. 11 is a block diagram of a shear wave velocity estimation apparatus according to an exemplary embodiment of the present application;

fig. 12 is a block diagram of a terminal according to an exemplary embodiment of the present application.

Detailed Description

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

When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.

In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "connected," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context. Furthermore, in the description of the present application, unless otherwise indicated, "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.

As used herein, the term "if" is optionally interpreted as "when..once.," at … …, "in response to a determination," or "in response to a detection," depending on the context. Similarly, the phrase "if determined … …" or "if detected (stated condition or event)" or "in response to detection (stated condition or event)" depending on the context.

In the field of hydrocarbon reservoir exploration, the formation is gradually depleted as the formation is more easily explored and exploited. Exploration and acquisition of relatively complex unconventional reservoirs is a major work object. Wherein, dense sandstone and shale in unconventional hydrocarbon reservoirs are represented and gradually become hot spot research objects for oil and gas exploration and development. Shale oil is a petroleum resource produced in unconventional reservoirs investigated by the methods provided herein. The shale oil is characterized by comprising the following components: the medium-high maturity, the complex rock components, the organic matter content of more than 2%, the porosity of 2-10%, the permeability of 0.0001 mD-0.1 mD and the source storage integrated continuous aggregation. In the manner of storing hydrocarbon resources, the hydrocarbon resources are lodged in the nanopore system in shale in an adsorbed state and a free state. In petrophysical simulation, shale has multiple mineral components and complex pore structures due to its contrast to conventional binary sandstones or mudstones. Therefore, the method and the device provide a scheme for analyzing the storage condition of the shale oil and gas reservoir based on the shale rock physical model, so that the storage quantity of the oil and gas reservoir in shale can be conveniently explored and analyzed, and the shale exploration efficiency is improved.

In some shale petrophysical modeling schemes, self Consistency (SC) models, differential equivalent medium (Differential Effective Medium, DEM) models, and Backus theory are included. Based on the above, one possible landing scenario is presented below.

In the first step, clay and kerogen are mixed by using self-consistent and differential equivalent (SCA+DEM) models to obtain kerogen-clay blocks with intercommunicating properties.

Second, a specified number and exact same of clay-kerogen blocks are rotated and superimposed to simulate shale layering. The elastic property of the clay blocks after rotation can be calculated by Bond transformation. The equivalent properties of clay block superposition of different shapes can be calculated by the Voigt-Reuss-Hill boundary model average.

Third, the equivalent modulus of brittle minerals other than clay and kerogen was calculated using Voigt-Reuss-Hill boundary model averaging.

And fourthly, using an equivalent substance formed by clay-kerogen blocks distributed in layers as a background, and sequentially adding the brittle mixture and the pores into a background medium by using a Differential Equivalent (DEM) model to obtain a final equivalent result.

Through the scheme formed by the four steps, the obtained shale petrophysical model can be used for analyzing oil and gas reservoirs, and the model emphasizes organic matters in shale. However, the following disadvantages exist. First, because the mineral components and pore structure of shale are complex, how the various mineral components and pore width to length ratios are found is an important component of petrophysical modeling, and this modeling approach is not involved. Second, when the Voigt-Reuss-Hill boundary model is applied, it is assumed that the mixture components are homogeneous and the rock is linear, elastic. However, in a practical multiphase medium, the distribution of stress strain is unpredictable and not uniform. The Voigt upper limit and Reuss lower limit are not sufficient to accurately calculate the equivalent of a multiphase material, and only provide a relatively broad upper and lower limit reference. The use of Voigt-Reuss-Hill average in this method to calculate the equivalent modulus for a variety of brittle minerals other than clay and kerogen is therefore not suitable. Third, the model does not relate to a method of mixing fluids in rock. Fourth, as can be seen from the four steps of the modeling method, the modeling process of the modeling method realizes the modeling process of the dry rock, and a fluid displacement model is not mentioned, so that the complete shale oil petrophysical modeling method is not calculated.

Referring to fig. 1, fig. 1 is a flowchart of a method for estimating a shear wave velocity according to an exemplary embodiment of the present application. The method for estimating the transverse wave velocity can be applied to a terminal. In fig. 1, the method for estimating the shear wave velocity includes:

in step 110, rock mineral composition of a rock sample mined from a shale reservoir is calculated, the rock mineral composition being indicative of mineral composition of the rock sample.

In the oil and gas exploration process, an exploratory person can sample a sample in a subterranean formation through a drill bit, so that a rock sample is obtained. The present application may be based on rock samples that have been collected.

Rock mineral components of the rock sample that have been acquired are acquired. It should be noted that the present application may be applied to determining the shear wave velocity of shale. The following will describe a rock sample as a shale sample.

Shale has very complex mineral components, including up to ten minerals such as quartz, feldspar, and dolomite. Finding the content of each mineral would be a huge effort and less return. Thus, the present application simplifies the complex components of rock samples into quartz, feldspar, calcite, dolomite and clay minerals depending on how much the mineral elasticity parameter characteristics and content are. At the same time, the present application will consider the shale reservoir characteristics and will also find the kerogen content. That is, in one manner of obtaining the rock mineral composition of a style sample, the present application will determine the respective content of quartz, feldspar, calcite, dolomite, and clay minerals in the rock sample.

From the above description, it is known that rock mineral compositions are used to indicate the content of various minerals contained in a rock sample.

In the implementation process of step 110, the present application further provides four ways of obtaining related data, which is described below.

(1) And (5) solving a dry clay point.

On the neutron-density intersection diagram and the sound wave-density intersection diagram, three-porosity curve skeleton points of the dry clay are determined by a triangle method from pure quartz points, free water points and constraint water points according to the distribution of data points and are used for subsequent well logging component model calculation and modeling parameters.

(2) And (5) obtaining the clay content.

The calculation of the clay content is generally carried out using a GR curve. However, due to the complex shale oil lithology, the GR curves do not reflect the change in lithology. Therefore, the method adopts a neutron-density intersection method to calculate the argillaceous content curve on the basis of dry clay point calculation.

(3) And (5) obtaining kerogen.

There are generally four methods for the calculation of kerogen content, namely Passey's formula, multivariate fitting, density and natural gamma spectroscopy. The principle of the Passey formula is that different coordinate scales are applied under the same coordinate, and the acoustic time difference curve is superposed on the resistivity curve. In a non-hydrocarbon-source rock interval, the resistivity and the porosity curves are parallel to each other and coincide with each other, and in a reservoir or a hydrocarbon-source rock interval rich in organic matters, an amplitude difference exists between the two curves, and the magnitude of the amplitude difference is indicative of the kerogen content, and the specific formula is as follows:

ΔlogR＝log(R/R _{Base line} )+K*(Δt-Δt _{Base line} )

In the above formula, TOC is kerogen content, R is resistivity, R _{Base line} For the resistivity base line, K is the scale factor, deltat is the acoustic time difference, deltat _{Base line} For the acoustic time difference base line, R ₀ For the vitrinite reflectance, B is the TOC value of the non-hydrocarbon rock layer.

Based on the actual accuracy measurement, in one possible way, the Passey formula method is selected to calculate the kerogen content.

(4) And (5) obtaining brittle minerals.

In the field of hydrocarbon reservoir exploration, an optimized logging interpretation method targets complete component model elements, and performs optimization solution on logging data sensitive to each component as input to obtain a complete rock component model. The optimized logging interpretation method can effectively reduce the influence of single data polynomials and noise, and obtain the optimal component model. In addition to the conventional curves, the method introduces element well uranium content curves and thorium content curves to calculate brittle minerals when the optimized well logging interpretation method is used.

Step 120, calculating a total porosity profile of the rock sample based on the shale content in the rock mineral fraction and a first parameter, the first parameter comprising a sonic time difference or density profile.

In the present application, the total porosity is calculated from the acoustic transit time or density curve by Wyleie mean equation based on the determination of the clay content, which is the total porosity curve calculated from the acoustic transit time curve. The specific formula is as follows:

In the above formula, v is the velocity of the whole rock sample, v _f Is the velocity of the rock matrix, v _m Is the velocity of the pore fluid and Φ is the porosity.

Step 130, calculating a water saturation curve of the rock sample based on the rock electrical parameters of the rock sample.

In this application, the water saturation is generally calculated by the Archie equation using resistivity and porosity curves. However, since the Alqi formula is an explanation method for pure rock, the influence of formation water is not considered, and two methods are derived. First, the Indonesia equation (Indonesia) applies to formations with lower mineralization of formation water. Second, simantoux is applicable to formations with higher mineralization of formation water.

Alqi formula: s is S _w ＝(a*b*R _w /R _t *Φ ^m ) ^1/n

In the above formula, S _w For water saturation, a, b, m and n are rock electrical parameters, typically constant in a certain region; r is R _w R is the resistivity of stratum water _t Is the true resistivity of the formation, Φ is the porosity.

In one possible application, if the formation water mineralization of the rock sample is relatively low, the water saturation curve may be determined using the Nissan equation.

Step 140, calculating the pore width-to-length ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample.

In one possible approach, the pore width to length ratio curve may take on theoretical values.

In another possible approach, the present application provides a way to determine the pore width to length ratio curve that is more closely related to the rock sample. That is, the present application can calculate the pore width to length ratio curve of a rock sample from the ratio of the target mineral content to the total mineral content in the rock sample.

Step 150, performing fluid displacement based on the plastic mineral equivalent modulus, the brittle mineral equivalent modulus, the rock skeleton equivalent modulus, the dry rock equivalent modulus and the fluid equivalent modulus to establish a petrophysical model of the rock sample.

It should be noted that the present application is capable of calculating a rock mineral composition curve, a total porosity curve, a water saturation curve, and a pore width to length ratio curve, and is capable of building a petrophysical model of a rock sample based on the above data. The present application provides a process for building a petrophysical model of a rock sample, as set forth below.

(1) Plastic mineral equivalent

Shale generally has better clay layering, more clay mineral species, and the elastic properties of different clay minerals are not exactly the same. At the same time, organic matter of different maturity (such as kerogen) also has an effect on shale heterogeneity. The distribution and interrelation of clay and organic matter in shale are considered as factors which must be considered in the shale model construction. The procedure of plastic mineral equivalence is described in two steps.

And (a 1) taking clay with the content of kerogen and the like, and mixing the clay with the clay by using a self-consistent model (SCA).

And (a 2) taking the residual clay as a background medium, taking the mixture obtained in the step (a 1) as a filler, and mixing the residual clay and the filler by utilizing a Differential Equivalent Model (DEM) to obtain the plastic mineral equivalent modulus of the kerogen-clay with the mutual communication property.

(2) Brittle mineral equivalent

In one possible way, if four brittle minerals are included in the rock sample, quartz, feldspar, dolomite and calcite, respectively. Wherein, the content of the quartz, the feldspar and the dolomite is basically equivalent, and the content of calcite is smaller. Therefore, the following equivalent method is adopted for the brittle minerals according to the content of the four brittle minerals.

And (b 1) mixing the brittle minerals with basically equivalent quartz, feldspar and dolomite by using a self-consistent model (SCA) capable of simultaneously and equivalently producing multiphase minerals.

And (b 2) taking the mixture obtained in the step (b 1) as a background medium, taking calcite with a small content as a filler, and mixing the calcite and the filler by utilizing a Differential Equivalent Model (DEM) to obtain the brittle mineral equivalent modulus.

(3) Rock skeleton equivalent

The plastic equivalent substance composed of clay and kerogen is used as a background medium, brittle equivalent substances such as quartz and dolomite are used as fillers, and the two materials are mixed by utilizing a Differential Equivalent Model (DEM) to obtain the rock skeleton equivalent modulus.

(4) Dry rock equivalent

And adding pores into the background medium by using a Differential Equivalent Model (DEM) by taking the rock skeleton as the background medium to obtain the equivalent modulus of the dry rock, wherein the pore width-to-length ratio is a pore width-to-length ratio curve obtained by the calculation.

(5) Fluid equivalent

Fluid properties were calculated from known temperature, pressure, oil density, formation water mineralization, gas to oil ratio using Batzle & Wang et al, and fluid mixing was performed using Brie exponential method.

(6) Fluid displacement

Because the shale layer under the oil saturation condition has obvious velocity dispersion phenomenon, the full-band Boris fluid displacement model is selected to put mixed fluid into dry rock, so that a shale equivalent model close to the actual condition is established.

Based on the processing of the above steps, the petrophysical model established in the present application is analyzed as follows. According to the method, the calculation method of the rock physical modeling related curve is subjected to contrast optimization, the prediction precision of the modeling related curve is guaranteed, and a good data foundation is laid for subsequent complex mineral component shale oil rock physical modeling. The mineral pore width-to-length ratio of the prior petrophysical modeling method is given as a theoretical constant value, and the pore width-to-length ratio curve is creatively calculated according to the content of each mineral at the depth point. The self-consistent model (SCA) +differential equivalent model (DEM) is used for the equivalence of the brittle minerals, the assumption that the components of the mixture are uniform and the rock is linear and elastic in the Voigt-Reuss-Hill boundary model is avoided, and the equivalence of the brittle minerals is more accurate. The full-band Boris fluid displacement model is selected, and compared with the Gassmann fluid displacement model with low frequency, the full-band Boris fluid displacement model is accurate in speed. The shale reservoir rock physical modeling process is clear, the rock physical model selected by each equivalent process is reasonable, and the method is a complete complex mineral component shale oil rock physical modeling method. The accuracy of the transverse wave speed predicted by the method is higher, the coincidence rate of the transverse wave speed predicted by the prior art and the actual measured transverse wave speed is 85% through the application of the test area to the floor, and the coincidence rate of the innovative technology is as high as 92%.

Step 160, estimating the shear wave velocity of the rock sample based on the petrophysical model.

In the present application, the shear wave velocity of the rock sample can be estimated based on the petrophysical model. After the shear wave velocity of the rock sample is acquired, the corresponding pre-stack elasticity parameters can be calculated. After obtaining the pre-stack elasticity parameters, a maximum level principal stress and a minimum level principal stress may be calculated. Based on the maximum horizontal principal stress and the minimum horizontal principal stress, the fracturing effect, the fracturing well stability, the crack extending direction, the form and the azimuth of the horizontal well can be obtained, so that the yield of the horizontal well is improved based on the data.

In summary, according to the method for estimating the shear wave velocity, after the rock sample is obtained, the pore width-to-length ratio curve of the model sample can be calculated, and then plastic mineral equivalent, brittle mineral equivalent, rock skeleton equivalent, dry rock equivalent, fluid equivalent and fluid replacement are performed, so that a petrophysical model of the rock sample is established, and the shear wave velocity of the rock sample can be estimated based on the petrophysical model. The rock physical model of the rock sample close to the actual shale reservoir is comprehensively built, so that the transverse wave speed estimation of the rock sample is accurate, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well zone selection and increased storage production.

Referring to fig. 2, fig. 2 is a flowchart of a method for estimating a shear wave velocity according to the embodiment shown in fig. 1. Steps 110 to 130 in the estimation of the transverse wave speed provided in fig. 2, and the execution manners of step 150 and step 160 are similar to those in fig. 1, and are not repeated here. In fig. 2, step 140 is alternatively performed from step 141 to step 145, as described below.

Step 141, determining the depth of acquisition of the rock sample.

In the embodiment of the application, the rock sample is recorded at the stratum depth when being collected, namely the collection depth of the rock sample. The application will determine the depth of acquisition of the rock sample, which will be recorded in the data of the rock sample.

Step 142, obtaining the target mineral content of each of n target minerals in the rock sample in the collection depth, and the theoretical value of the pore width-length ratio of each of the n target minerals.

The rock sample comprises n target minerals, wherein n is a positive integer.

It should be noted that if the rock sample includes 3 target minerals, three sets of data are required to be acquired in the present application. Each set of data includes the set of target mineral contents and a theoretical value for the pore width to length ratio of the set of target minerals.

Step 143, determining the total mineral content in the rock sample at the depth of acquisition.

In embodiments of the present application, the terminal is capable of determining the total mineral content in the rock sample as a function of the depth of acquisition. Wherein different acquisition depths will correspond to different total mineral contents.

And 144, calculating the pore width-length ratio component of the target mineral according to the total mineral content, the target mineral content and the pore width-length ratio theoretical value.

In the embodiment of the application, the terminal can calculate the pore width length ratio component of a target mineral according to the target mineral content and the pore width length ratio theoretical value of the target mineral and the total mineral content. For example, if the rock sample contains 3 kinds of target minerals in total, this step can calculate the pore width-length ratio components corresponding to the 3 kinds of target minerals.

In step 144, four different schemes for calculating the pore width to length ratio component of the target mineral may be included, as described below.

Scheme one, including step 1441 and step 1442.

Step 1441 takes the quotient of the target mineral content and the total mineral content as a first intermediate variable.

And 1442, multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain the aperture width-to-length ratio component of the target mineral.

If the pore width-to-length ratio curve of the rock sample is calculated based on scheme one, the calculation formula can be as follows.

Asp＝∑((V′/V _T )*asP′)

Wherein Asp is pore width-to-length ratio curve, V' is mineral content, V _T The asp' is a theoretical value of a certain mineral pore width-length ratio.

Scheme two, including step 1441, step 1443, step 1444, and step 1445.

Step 1443, multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain a second intermediate parameter.

Step 1444, a first constant term corresponding to the target mineral is obtained.

Step 1445, taking the sum of the first constant term and the second intermediate parameter corresponding to the target mineral as the pore width-length ratio component of the target mineral.

If the pore width to length ratio curve of the rock sample is calculated based on scheme two, the calculation formula can be as follows.

Asp＝∑((V′/V _T )*asp′+C ₁ )

Wherein Asp is pore width-to-length ratio curve, V' is mineral content, V _T The asp' is a theoretical value of the aperture width-length ratio of a certain mineral, C ₁ Is a first constant term.

Scheme three, including step 1441, step 1446, step 1447, and step 1448.

Step 1446, multiplying the first intermediate parameter by the theoretical value of the aperture width to length ratio to obtain a third intermediate parameter.

In step 1447, a first coefficient corresponding to the target mineral is obtained.

Step 1448, taking the product of the first coefficient corresponding to the target mineral and the third intermediate parameter as the aperture width-to-length ratio component of the target mineral.

If the pore width to length ratio curve of the rock sample is calculated based on scheme three, the calculation formula can be as follows.

Asp＝∑(K ₁ (V′/V _T )*asp′)

Wherein Asp is pore width-to-length ratio curve, V' is mineral content, V _T The asp' is a theoretical value of the aperture width-length ratio of a certain mineral, K ₁ Corresponds to the target mineralIs a first coefficient of (a).

Scheme three, including step 1441, step 1446, step 1447, step 14481, step 14482, and step 14483.

Step 1447, obtaining a second coefficient corresponding to the target mineral.

Step 14481, taking the product of the second coefficient of the target mineral and the third intermediate parameter as the fourth intermediate parameter.

Step 14482, obtaining a second constant term corresponding to the target mineral.

And 14483, taking the sum of the second constant terms corresponding to the fourth intermediate parameter and the target mineral as the pore width-length ratio component of the target mineral.

If the pore width to length ratio curve of the rock sample is calculated based on scheme four, the calculation formula can be as follows.

Asp＝∑(K ₂ (V′/V _T )*asp′+C ₂ )

Wherein Asp is pore width-to-length ratio curve, V' is mineral content, V _T The asp' is a theoretical value of the aperture width-length ratio of a certain mineral, K ₂ For the second coefficient corresponding to the target mineral, C ₂ Is a second constant term.

And 145, accumulating the pore width-to-length ratio components of each of the n target minerals to obtain a pore width-to-length ratio curve of the rock sample.

In the embodiment of the application, the terminal adds up the pore width and length ratio components corresponding to each target mineral, and takes the added sum value as a pore width and length ratio curve of the rock sample.

In summary, the method for estimating the transverse wave velocity according to the present embodiment can calculate the aperture width-to-length ratio, which is generally used as a constant, as a calculable parameter, where the aperture width-to-length ratio can be determined by a plurality of calculation methods, and a constant term or coefficient related to the target mineral is provided in each calculation method, so that the aperture width-to-length ratio can be closer to the actual situation. Therefore, the rock physical model constructed by the method is closer to the actual stratum condition, the true transverse wave speed can be obtained, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well area selection and storage and upper production increase.

Referring to fig. 3, fig. 3 is a flowchart of another method for estimating a shear wave velocity according to the embodiment shown in fig. 1. The method for estimating the transverse wave velocity can be applied to a terminal. In fig. 3, the method for estimating the shear wave velocity includes:

in step 301, rock samples are mined from shale reservoirs, and data required to build a petrophysical model of the rock samples is calculated based on sonic time difference curves, density curves and petroelectrical parameters of the rock samples, the required data including mineral composition curves, total porosity curves and water saturation curves.

Step 302, calculating a pore width-to-length ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample.

Step 303, mixing by using a self-consistent model and a differential equivalent model based on mineral components of the rock sample to obtain plastic mineral equivalent modulus and brittle mineral equivalent modulus of the rock sample respectively.

Step 304, mixing by utilizing a differential equivalent model based on the plastic mineral equivalent substance and the brittle mineral equivalent substance of the rock sample to obtain the rock skeleton equivalent modulus of the rock sample.

Step 305, based on the rock skeleton and porosity of the rock sample, mixing by using a differential equivalent model to obtain the dry rock equivalent modulus of the rock sample.

Step 306, based on the water saturation of the rock sample, performing fluid mixing by using Brie exponential method to obtain the fluid equivalent modulus of the rock sample.

Step 307, performing fluid replacement by using the Boris fluid replacement model based on the dry rock and the mixed fluid of the rock sample, thereby establishing a petrophysical model of the rock sample.

Step 308, estimating the shear wave velocity of the rock sample based on the petrophysical model.

In summary, after the rock sample is obtained, the pore width-to-length ratio curve of the model sample can be calculated, and then plastic mineral equivalent, brittle mineral equivalent, rock skeleton equivalent, dry rock equivalent, fluid equivalent and fluid displacement are performed, so that a rock physical model of the rock sample is established, and the transverse wave velocity of the rock sample can be estimated based on the rock physical model. The rock physical model of the rock sample close to the actual shale reservoir is comprehensively built, so that the transverse wave speed estimation of the rock sample is accurate, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well zone selection and increased storage production.

Based on the scheme disclosed in the previous embodiment, the application can also run a corresponding program through the terminal to realize a method for estimating the transverse wave speed, and one of the landing embodiments can be referred to as follows.

In one possible embodiment of the present application, basin a, sink B is selected as the collection area for the rock sample. Wherein, the target layer is determined to be collected from a specified three-dimensional area, and the burial depth of the target layer binary-series reed canary grass ditch group is 3000-3500 m. The vertical well yield is low due to the influence of low-hole and low-permeability quality of desserts, the vertical well yield is mainly increased by virtue of the horizontal well, the ground stress distribution condition is a key factor for improving the horizontal well fracturing transformation yield, and the extending direction, the shape and the azimuth of the fracturing cracks are determined. The pre-stack elastic parameters are used in the calculation of the maximum horizontal main stress and the minimum horizontal main stress, and accurate transverse wave velocity data are needed for calculating the high-precision pre-stack elastic parameters. Although there are many ways to calculate shear wave velocity, a reasonable petrophysical model remains the most efficient way to calculate shear wave velocity. Therefore, how to accurately find the shear wave velocity is a key factor in accurately predicting the ground stress distribution.

The research area accurately predicts the transverse wave speed and faces two problems to be solved.

(1) Problem one: since shale has complex mineral composition and pore structure, accurate calculation of petrophysical modeling correlation curves is the basis of modeling.

The solution is as follows: and calculating a plurality of methods for comparison analysis of each curve to obtain an optimal method suitable for the research area.

Fig. 4 is a graph of the results of calculating the kerogen (TOC) content using the Passey formula, the multivariate fitting method, the density method, and the natural gamma spectroscopy, respectively, provided in the present application. FIG. 5 is a graph of the comparison of results calculated by four methods with measured kerogen (TOC) content provided herein. The kerogen content obtained by the Passey formula method can be obtained from the comparison chart and is best matched with the actual measurement on the well. Fig. 6 is a graph of the calculation result of a petrophysical modeling correlation curve provided by the application. According to analysis of each curve correlation algorithm, the method finally uses a neutron-density intersection method to calculate a argillaceous content curve, uses an optimized logging interpretation method to calculate a brittle mineral content curve, uses a Wyleie average equation of a sound wave time difference curve to calculate a total porosity curve, uses an Indonesia equation (Indoneseian) of an improved Alqi formula to calculate a water saturation curve, and uses an aperture width-length ratio calculation formula of the invention to calculate an aperture width-length ratio curve. FIG. 7 is a graph of the intersection of brittle mineral content and measured content for an optimized log interpretation method provided herein, with data points generally distributed about a 45 degree line.

The application effect is as follows: the correlation methods of various curve calculation are used for comparison and analysis, so that the prediction result and the actual measurement result of the rock physical modeling correlation curve have the highest coincidence degree, and a good data foundation is laid for the subsequent rock physical modeling of the shale oil with complex mineral components.

(2) And a second problem: although students at home and abroad have a certain research and achievement on the shale petrophysical modeling technology, a shale oil petrophysical modeling method suitable for the research area is not complete.

The solution is as follows: on the basis of sufficient technical investigation, a shale oil petrophysical modeling method of complex mineral components is formulated.

As shown in fig. 8 to 10, accurate shear wave velocity data is obtained by a complex mineral component shale oil petrophysical modeling method. FIG. 8 is a flow chart of the physical modeling of shale oil rock with complex mineral components, wherein the plastic mineral and the brittle mineral are mixed by SCA (self-consistent model) +DEM (differential equivalent model) to obtain the plastic mineral equivalent modulus and the brittle mineral equivalent modulus; taking plastic equivalent substances as a background, sequentially adding a brittle mixture and pores into a background medium by utilizing a Differential Equivalent Model (DEM) to obtain a dry rock equivalent modulus; mixing the fluids by using a Brie index method according to known temperature, pressure, oil density, formation water mineralization degree and gas-oil ratio; and placing the mixed fluid into the dry rock through a full-band Boris fluid displacement model, so that a shale equivalent model close to the actual situation is established. Fig. 9 is a graph of results of longitudinal wave velocity, density, and transverse wave velocity obtained using the shale oil petrophysical modeling method of the present application. FIG. 10 is a graph of the intersection of shear wave velocity and measured shear wave velocity using the shale oil petrophysical modeling method of the present application, with data points generally distributed about a 45 degree line.

The application effect is as follows: the complex mineral component shale oil petrophysical modeling method is applied to solve the problem of low shale oil petrophysical modeling precision, so that the coincidence rate of the predicted transverse wave speed and the actually measured transverse wave speed is as high as 92%, and a solid foundation is laid for pre-stack elastic parameter research.

The prediction experiment of the method proves that the multi-component equivalent petrophysical modeling method is based, the effective characterization of multiple mineral components of shale complex lithology is realized, high-precision transverse wave speed data can be obtained, a method foundation is laid for predicting various pressure and ground stress of a stratum by utilizing seismic data, and a powerful technical support is provided for subsequent shale oil horizontal well selection and increased storage production.

In another floor-standing embodiment provided herein, the following is provided.

(1) The petrophysical modeling correlation curve is found as in fig. 4 to 7.

(1) Determination of rock mineral composition

Shale has very complex mineral components, including quartz, dolomite and the like, and if the content of the shale is calculated for each mineral, the content of kerogen is not realistic, so the complex components are simplified into quartz, feldspar, calcite, dolomite and clay minerals through analysis of the characteristics of mineral elasticity parameters and the content of the mineral elasticity parameters, and the content of kerogen is also required to be calculated by considering the characteristics of shale reservoirs.

a. Determination of Dry Clay Point

On the neutron-density intersection diagram and the sound wave-density intersection diagram, three-porosity curve skeleton points of the dry clay are determined by a triangle method from pure quartz points, free water points and constraint water points according to the distribution of data points, and the values of sound wave time difference, density and neutron porosity of the dry clay point of the work area are (97,2.66,0.55) and are used for subsequent logging component model calculation and modeling parameters.

b. Determination of the shale content

The calculation of the shale content generally uses a GR curve, but the shale oil lithology complex GR curve cannot reflect the lithology change, so the shale oil lithology complex GR curve is calculated by adopting a neutron-density intersection method on the basis of dry clay point calculation.

c. Determination of kerogen

There are generally four methods for the calculation of kerogen content, namely Passey's formula, multivariate fitting, density, natural gamma spectroscopy. The principle of the Passey formula method is that different coordinate scales are applied under the same coordinate, an acoustic time difference curve is superimposed on a resistivity curve, in a non-hydrocarbon source stratum section, the resistivity and the porosity curves are parallel and coincide with each other, and in a reservoir or a hydrocarbon source stratum section rich in organic matters, amplitude difference exists between the two curves, the magnitude of the difference value is used for representing the content of kerogen, and the specific formula is as follows:

ΔlogR＝log(R/R _{Base line} )+K*(Δt-Δt _{Base line} )

The four methods are used for obtaining the content of the kerogen respectively, the results are shown in figure 4, and the content of the kerogen is calculated by selecting a Passey formula method and comparing the calculation results of the four methods, and is shown in figure 5.

d. Determination of brittle minerals

The optimized logging interpretation method takes complete component model elements as targets, takes logging data sensitive to each component as input to carry out optimized solution so as to obtain a complete rock component model, and can effectively reduce the influence of single data polynomials and noise to obtain an optimal component model. When the optimized logging interpretation method is used, besides a conventional curve, elemental logging uranium and thorium content curves are introduced to calculate brittle minerals.

(2) Determination of the Total porosity curve

On the basis of the determination of the clay content, the total porosity is determined by a Wyle average equation from an acoustic time difference or density curve, and the total porosity is determined from an acoustic time difference curve. The specific formula is as follows:

(3) Determination of the Water saturation curve

The water saturation is generally calculated by the alchi equation using the resistivity and porosity curves, but since the alchi equation is an interpretation of pure rock, it does not take into account the influence of formation water itself, and thus two methods are derived. Indonesia equation (Indonesia) is applicable to formations with lower formation water mineralization.

The Simantoux equation is suitable for stratum with higher mineralization degree of stratum water.

Alqi formula: s is S _w ＝(a*b*R _w /R _t *Φ ^m ) ^1/n

The formation water mineralization of this work area was 12000ppm and was relatively low, so the Indonesia equation was used to determine the water saturation curve.

(4) Obtaining pore width-length ratio curve

The mineral pore width-to-length ratio of the prior petrophysical modeling method is given as a theoretical constant value, and the pore width-to-length ratio curve is creatively calculated according to the content of each mineral at the depth point. The specific formula is as follows:

Asp＝∑((V′/V _T )*asp′)

Wherein Asp is pore width-to-length ratio curve, V' is mineral content, V _T The asp' is a theoretical value of a certain mineral pore width-length ratio. The six minerals in the working area are quartz, feldspar, calcite, dolomite, clay mineral and kerogen respectively, wherein the theoretical value of the pore width-to-length ratio of the quartz to the feldspar is 0.12, the theoretical value of the pore width-to-length ratio of the calcite to the dolomite is 0.8, and the theoretical value of the pore width-to-length ratio of the clay mineral to the kerogen is 0.05.

The final petrophysical modeling related curve is calculated by the related algorithm of the various curves, and the predicted result and the measured result on the well are the highest in agreement, as shown in figure 6.

(2) Shale oil petrophysical modeling flow is as shown in fig. 8-10.

The complex mineral component shale oil petrophysical modeling flow is shown in fig. 8, and the specific implementation steps are as follows:

(1) plastic mineral equivalent

Shale generally has better clay layering, more clay mineral types, and different clay minerals have different elastic properties, and organic matters (such as kerogen) with different maturity also have an effect on the heterogeneity of shale. The distribution and interrelation of clay and organic matter in shale are considered as factors which must be considered in the shale model construction.

a. The same amount of clay as kerogen was taken and mixed using a self-consistent model (SCA).

b. Mixing the residual clay with the mixture obtained in the step a as a filler by utilizing a Differential Equivalent Model (DEM) to obtain the plastic mineral equivalent modulus of the kerogen-clay with the mutual communication property.

(2) Brittle mineral equivalent

The four brittle minerals of the research area have basically equivalent contents of quartz, feldspar and dolomite, and smaller content of calcite, so the following equivalent method is adopted for the brittle minerals according to the content of the four brittle minerals.

a. Brittle minerals such as quartz with basically equivalent mineral contents are mixed by using a self-consistent model (SCA) capable of simultaneously and equivalently producing multiphase minerals.

b. And c, taking the mixture obtained in the step a as a background medium, taking calcite with a small content as a filler, and mixing the calcite with the background medium by utilizing a Differential Equivalent Model (DEM) to obtain the equivalent modulus of the brittle mineral.

(3) Rock skeleton equivalent

The plastic equivalent substance composed of clay and kerogen is used as a background medium, brittle equivalent substances such as quartz and dolomite are used as fillers, and the clay and kerogen are mixed by utilizing a Differential Equivalent Model (DEM) to obtain the rock skeleton equivalent modulus.

(4) Dry rock equivalent

(5) Fluid equivalent

(6) Fluid displacement

By implementing the complex mineral component shale oil petrophysical modeling method, the obtained longitudinal wave speed, density and transverse wave speed are shown in figure 9, and the coincidence degree of the predicted transverse wave speed and the actually measured transverse wave speed is as high as 92 percent, as shown in figure 10.

The following are device embodiments of the present application, which may be used to perform method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

Referring to fig. 11, fig. 11 is a block diagram illustrating a transverse wave speed estimation apparatus according to an exemplary embodiment of the present application. The means for estimating the shear wave velocity may be implemented as all or part of the terminal by software, hardware or a combination of both. The device comprises:

A modeling data calculation module 1010 for mining a rock sample from a shale reservoir, calculating data required to build a petrophysical model of the rock sample based on a sonic time difference curve, a density curve, and petroelectrical parameters of the rock sample, the required data including a mineral composition curve, a total porosity curve, and a water saturation curve;

an aperture ratio calculation module 1020 for calculating an aperture ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample;

the rock matrix equivalent module 1030 is configured to obtain a plastic mineral equivalent modulus and a brittle mineral equivalent modulus of the rock sample respectively by mixing with a self-consistent model and a differential equivalent model based on mineral components of the rock sample;

the rock skeleton equivalent module 1040 is configured to obtain a rock skeleton equivalent modulus of the rock sample by mixing with a differential equivalent model based on a plastic mineral equivalent substance and a brittle mineral equivalent substance of the rock sample;

the dry rock equivalent module 1050 is configured to obtain a dry rock equivalent modulus of the rock sample by mixing with a differential equivalent model based on a rock skeleton and porosity of the rock sample;

A fluid equivalent module 1060 for performing fluid mixing by Brie index method based on the water saturation of the rock sample to obtain the fluid equivalent modulus of the rock sample;

a fluid displacement module 1070 for performing fluid displacement using a Boris fluid displacement model based on the dry rock and the mixed fluid of the rock sample, thereby creating a petrophysical model of the rock sample;

a shear wave velocity estimation module 1080 for estimating a shear wave velocity of the rock sample based on the petrophysical model.

In an alternative embodiment, the aperture width to length ratio calculation module 1020 is configured to determine the depth of acquisition of the rock sample; acquiring the target mineral content of each of n target minerals in the rock sample in the acquisition depth, and the theoretical value of the pore width-to-length ratio of each of the n target minerals; determining the total mineral content in the rock sample at the acquisition depth; calculating to obtain a pore width-to-length ratio component of the target mineral according to the total mineral content, the target mineral content and the pore width-to-length ratio theoretical value; accumulating the pore width-to-length ratio components of each of n target minerals to obtain the pore width-to-length ratio curve of the rock sample, wherein the rock sample comprises n target minerals, and n is a positive integer.

In an alternative embodiment, the pore width to length ratio calculation module 1020 is configured to take the quotient of the target mineral content and the total mineral content as a first intermediate parameter; multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain the aperture width-to-length ratio component.

In an alternative embodiment, the aperture width-to-length ratio calculating module 1020 is configured to multiply the first intermediate parameter with the aperture width-to-length ratio theoretical value to obtain a second intermediate parameter; acquiring a first constant term corresponding to the target mineral; and taking the sum of the first constant term corresponding to the target mineral and the second intermediate parameter as the pore width-to-length ratio component of the target mineral.

In an alternative embodiment, the aperture width-to-length ratio calculating module 1020 is configured to multiply the first intermediate parameter with the aperture width-to-length ratio theoretical value to obtain a third intermediate parameter; acquiring a first coefficient corresponding to the target mineral; and taking the product of the first coefficient corresponding to the target mineral and the third intermediate parameter as the pore width-to-length ratio component of the target mineral.

In an alternative embodiment, the aperture width-to-length ratio calculating module 1020 is configured to multiply the first intermediate parameter with the aperture width-to-length ratio theoretical value to obtain a third intermediate parameter; acquiring a second coefficient corresponding to the target mineral; taking the product of the second coefficient of the target mineral and the third intermediate parameter as a fourth intermediate parameter; acquiring a second constant term corresponding to the target mineral; and taking the sum of the second constant terms corresponding to the fourth intermediate parameter and the target mineral as the pore width-to-length ratio component of the target mineral.

In summary, according to the device for estimating the transverse wave velocity, the rock mineral component of the rock sample can be calculated, the total porosity curve of the rock sample can be calculated based on the clay content and the first parameter in the rock mineral component, the water saturation curve of the rock sample can be calculated based on the rock electrical parameter of the rock sample, the aperture width-to-length ratio curve of the rock sample can be calculated according to the ratio of the target mineral content to the total mineral content in the rock sample, and finally the fluid replacement can be performed based on the plastic mineral equivalent modulus, the brittle mineral equivalent modulus, the rock skeleton equivalent modulus, the dry rock equivalent modulus and the fluid equivalent modulus, so that the petrophysical model of the rock sample can be established, and the transverse wave velocity of the rock sample can be estimated based on the petrophysical model. Because the rock physical model of the rock sample close to the actual shale reservoir is comprehensively built, the transverse wave velocity estimation of the rock sample is accurate, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and a powerful technical support is provided for subsequent shale oil horizontal well area selection and increased storage production.

Optionally, the device for estimating the transverse wave velocity provided by the application can calculate the aperture width-to-length ratio which is usually used as a constant as a calculable parameter, wherein the aperture width-to-length ratio can be determined by a plurality of calculation modes, and constant items or coefficients related to the target mineral are provided in each calculation mode, so that the aperture width-to-length ratio can be closer to the actual situation. Therefore, the rock physical model constructed by the method is closer to the actual stratum condition, the true transverse wave speed can be obtained, a method foundation is laid for predicting various pressure and ground stress of the stratum by utilizing the seismic data, and powerful technical support is provided for subsequent shale oil horizontal well area selection and storage and upper production increase.

The method for estimating the transverse wave speed, which is shown in the embodiment of the application, can be applied to a terminal, and the terminal has a transverse wave speed estimation function. The terminal may comprise a laptop, desktop, all-in-one, server, or workstation device.

Referring to fig. 12, fig. 12 is a block diagram of a terminal according to an exemplary embodiment of the present application, where, as shown in fig. 12, the terminal includes a processor 1120 and a memory 1140, where at least one instruction is stored in the memory 1140, and the instruction is loaded and executed by the processor 1120 to implement a method for estimating a transverse wave velocity according to various method embodiments of the present application.

In the present application, terminal 1100 extracts rock samples from shale reservoirs, calculates data required to build a petrophysical model of the rock samples based on sonic time difference curves, density curves, and petroelectrical parameters of the rock samples, the required data including mineral composition curves, total porosity curves, and water saturation curves; calculating a pore width-to-length ratio curve of the rock sample according to the ratio of the target mineral content to the total mineral content in the rock sample; mixing by utilizing a self-consistent model and a differential equivalent model based on mineral components of the rock sample to respectively obtain plastic mineral equivalent modulus and brittle mineral equivalent modulus of the rock sample; based on the plastic mineral equivalent substances and the brittle mineral equivalent substances of the rock sample, mixing by utilizing a differential equivalent model to obtain the rock skeleton equivalent modulus of the rock sample; based on the rock skeleton and the porosity of the rock sample, mixing by utilizing a differential equivalent model to obtain the dry rock equivalent modulus of the rock sample; based on the water saturation of the rock sample, carrying out fluid mixing by utilizing a Brie index method to obtain the fluid equivalent modulus of the rock sample; performing fluid replacement by using a Boris fluid replacement model based on the dry rock and mixed fluid of the rock sample, thereby establishing a petrophysical model of the rock sample; based on the petrophysical model, the shear wave velocity of the rock sample is estimated.

Processor 1120 may include one or more processing cores. Processor 1120 connects various portions of the overall terminal 1100 using various interfaces and lines, performs various functions of the terminal 1100, and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in memory 1140, and invoking data stored in memory 1140. Alternatively, the processor 1120 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 1120 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 1120 and may be implemented by a single chip.

The Memory 1140 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (ROM). Optionally, the memory 1140 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 1140 may be used to store instructions, programs, code sets, or instruction sets. The memory 1140 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (e.g., a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described below, etc.; the storage data area may store data and the like referred to in the following respective method embodiments.

Embodiments of the present application also provide a computer readable medium storing at least one instruction that is loaded and executed by the processor to implement the method of estimating a shear wave velocity as described in the above embodiments.

It should be noted that: in the above embodiment, when the method for estimating the transverse wave velocity is executed, only the division of the functional modules is used for illustration, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the apparatus for estimating the transverse wave velocity provided in the above embodiment and the method embodiment for estimating the transverse wave velocity belong to the same concept, and detailed implementation processes of the apparatus and the method embodiment are detailed and will not be described herein.

The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.

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 for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The above description is merely illustrative of the possible embodiments of the present application and is not intended to limit the present application, but any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the present application are intended to be included within the scope of the present application.

Claims

1. A method of estimating shear wave velocity, the method comprising:

2. The method of claim 1, wherein the rock sample includes n target minerals, n being a positive integer, and wherein calculating the pore width to length ratio curve of the rock sample based on the ratio of target mineral content to total mineral content in the rock sample comprises:

Determining the acquisition depth of the rock sample;

acquiring the target mineral content of each of n target minerals in the rock sample in the acquisition depth, and the theoretical value of the pore width-to-length ratio of each of the n target minerals;

determining the total mineral content in the rock sample at the acquisition depth;

calculating to obtain a pore width-to-length ratio component of the target mineral according to the total mineral content, the target mineral content and the pore width-to-length ratio theoretical value;

accumulating the pore width-to-length ratio components of each of the n target minerals to obtain the pore width-to-length ratio curve of the rock sample.

3. The method of claim 2, wherein calculating a pore width to length ratio component of the target mineral based on the total mineral content, the target mineral content, and the pore width to length ratio theoretical value comprises:

taking the quotient of the target mineral content and the total mineral content as a first intermediate parameter;

multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain the aperture width-to-length ratio component of the target mineral.

4. A method according to claim 3, wherein said multiplying said first intermediate parameter by said theoretical value of void width to length ratio to obtain said void width to length ratio component of said target mineral comprises:

Multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain a second intermediate parameter;

acquiring a first constant term corresponding to the target mineral;

and taking the sum of the first constant term corresponding to the target mineral and the second intermediate parameter as the pore width-to-length ratio component of the target mineral.

5. A method according to claim 3, wherein said multiplying said first intermediate parameter by said theoretical value of void width to length ratio to obtain said void width to length ratio component of said target mineral comprises:

multiplying the first intermediate parameter by the theoretical value of the aperture width-to-length ratio to obtain a third intermediate parameter;

acquiring a first coefficient corresponding to the target mineral;

and taking the product of the first coefficient corresponding to the target mineral and the third intermediate parameter as the pore width-to-length ratio component of the target mineral.

6. A method according to claim 3, wherein said multiplying said first intermediate parameter by said theoretical value of void width to length ratio to obtain said void width to length ratio component of said target mineral comprises:

Acquiring a second coefficient corresponding to the target mineral;

taking the product of the second coefficient of the target mineral and the third intermediate parameter as a fourth intermediate parameter;

acquiring a second constant term corresponding to the target mineral;

and taking the sum of the second constant terms corresponding to the fourth intermediate parameter and the target mineral as the pore width-to-length ratio component of the target mineral.

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

mixing the kerogen and the clay with the same content as the kerogen by using a self-consistent model to obtain a first mixture;

and mixing the first background medium and the filler by using the differential equivalent model by taking the clay which is remained after the clay with the content of kerogen and the like is taken as a first background medium and taking the first mixture as the filler, so as to obtain the plastic mineral equivalent modulus of the rock sample of the kerogen-clay with the intercommunicating property.

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

mixing the brittle minerals with the equivalent content of (p-1) by using a self-consistent model to obtain a second mixture, wherein p is a positive integer greater than 1;

And taking the second mixture as a second background medium, taking brittle minerals except the (p-1) brittle minerals in the target minerals as fillers, and mixing the second background medium and the fillers by utilizing a differential equivalent model to obtain the brittle mineral equivalent modulus of the rock sample.

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

and taking the rock skeleton as a third background medium, taking the pore width-to-length ratio curve as the shape characteristic of the pore, and adding the pore into the third background medium by utilizing a differential equivalent model to obtain the dry rock equivalent modulus of the rock sample.

10. An apparatus for estimating shear wave velocity, the apparatus comprising: