CN111208580A - Method and device for determining heterogeneity of shale gas reservoir - Google Patents
Method and device for determining heterogeneity of shale gas reservoir Download PDFInfo
- Publication number
- CN111208580A CN111208580A CN202010181237.XA CN202010181237A CN111208580A CN 111208580 A CN111208580 A CN 111208580A CN 202010181237 A CN202010181237 A CN 202010181237A CN 111208580 A CN111208580 A CN 111208580A
- Authority
- CN
- China
- Prior art keywords
- eigenmode
- fracturing
- pressure data
- functions
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
Abstract
The application provides a method and a device for determining heterogeneity of a shale gas reservoir, wherein the method comprises the following steps: acquiring casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period; performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; fourier transformation is carried out on the plurality of eigenmode functions of each fracturing section, and a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is obtained; and determining the heterogeneity of each fractured section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fractured section. By the scheme, the overall heterogeneous condition of the target shale gas reservoir can be truly and accurately determined, and the target shale gas reservoir can be more efficiently developed.
Description
Technical Field
The application relates to the technical field of geological exploration, in particular to a method and a device for determining heterogeneity of a shale gas reservoir.
Background
Reservoir heterogeneity refers to the property of the reservoir that varies with its spatial location, which can be mainly manifested in heterogeneity of rock material composition and in pore space, and is a major factor affecting subsurface fluid movement and ultimate recovery.
The existing method for determining the heterogeneity of the shale gas reservoir usually comprises the steps of collecting core samples of the shale gas reservoir at multiple depths, testing the properties of each core sample, and determining the heterogeneity of the whole reservoir by using a statistical method; or the variation condition of the reservoir property is obtained by using a mathematical method (such as a variation coefficient method, a Lorentz coefficient method and the like) based on geophysical logging data, so that the heterogeneity of the shale gas reservoir is determined.
However, because the geological structure distribution in the shale gas reservoir is changeable, the existing shale gas reservoir heterogeneity evaluation method usually adopts a core sample with a smaller data scale or logging data with limited resolution, so that the heterogeneity evaluation is mostly concentrated on a near-well reservoir, the heterogeneity of a far-well reservoir which cannot be represented by experimental data or logging interpretation data cannot be effectively evaluated, the evaluation range is limited, and the overall heterogeneity condition of the shale gas reservoir is difficult to truly and accurately reflect.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining the heterogeneity of a shale gas reservoir, and aims to solve the problems that the reservoir heterogeneity represented by the method in the prior art is low in precision and limited in evaluation range.
The embodiment of the application provides a method for determining heterogeneity of a shale gas reservoir, which comprises the following steps: acquiring casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period; performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; fourier transformation is carried out on the plurality of eigenmode functions of each fracturing section, and a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is obtained; and determining the heterogeneity of each fractured section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fractured section.
In one embodiment, determining the heterogeneity of each fractured segment of the target shale gas reservoir according to the fourier energy spectrum corresponding to each of the plurality of eigenmode functions of each fractured segment comprises: determining a spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section; and determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
In one embodiment, the starting point of the preset time period is a time point corresponding to ten percent reduction of the casing pressure data from the highest point in the hydraulic fracturing construction curve, and the end point of the preset time period is a time point corresponding to reduction of the casing pressure data to the reservoir pressure in the hydraulic fracturing construction curve.
In one embodiment, performing empirical mode decomposition based on casing pressure data of each of the plurality of fracture zones to obtain a plurality of eigenmode functions corresponding to each fracture zone includes: acquiring all maximum value points and minimum value points of the casing pressure data of the target fracturing section along with time change; fitting to form an upper envelope line by utilizing a cubic spline interpolation function based on all maximum value points of the casing pressure data of the target fracturing section along with time change; fitting by utilizing a cubic spline interpolation function to form a lower envelope line based on all minimum value points of the casing pressure data of the target fracturing section along with time change; determining the mean value of the upper envelope line and the lower envelope line based on the upper envelope line and the lower envelope line; determining casing pressure data residual error of the target fracturing section based on the mean value of the upper envelope line and the lower envelope line; determining whether the number of local zero points and zero points of casing pressure data residual errors of a target fracturing section is equal to or different from one point, and whether the mean value of an upper envelope line and a lower envelope line is 0; and under the condition that the local zero point and the zero point of the casing pressure data residual error of the target fracturing section are equal or different by one point and the mean value of the upper envelope line and the lower envelope line is 0, taking the casing pressure data residual error of the target fracturing section as an eigenmode function obtained by decomposition.
In one embodiment, the fourier transforming the plurality of eigenmode functions of each fracture section to obtain a fourier energy spectrum corresponding to each eigenmode function of the plurality of eigenmode functions of each fracture section includes: fourier transformation is carried out on the plurality of eigenmode functions of each fracturing section, and a Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is obtained; and determining a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
In one embodiment, determining a spectrally weighted average wave number for each of the plurality of eigenmode functions for each fracture zone based on the fourier energy spectrum for each of the plurality of eigenmode functions for each fracture zone comprises determining a spectrally weighted average wave number for each of the plurality of eigenmode functions for each fracture zone according to the following equation:
wherein k isn,mFor the spectral weighted average wavenumber, S, corresponding to the mth eigenmode function of the nth fracture zonen,m(k) A fourier energy spectrum corresponding to an mth eigenmode function of the nth fracturing stage, where N is 1,2n，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone.
In one embodiment, determining the heterogeneity of each fractured segment of the target shale gas reservoir according to the spectrally weighted average wavenumber corresponding to each eigenmode function of the plurality of eigenmode functions of each fractured segment comprises: and fitting the spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section with the serial number of each eigenmode function in the plurality of eigenmode functions of each fracturing section to obtain a heterogeneous index, wherein the heterogeneous index is in negative correlation with the strength of non-homogeneity.
The embodiment of the present application further provides a device for determining heterogeneity of a shale gas reservoir, including: the acquisition module is used for acquiring casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period; the decomposition module is used for carrying out empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; the transformation module is used for carrying out Fourier transformation on the plurality of eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section; and the determining module is used for determining the heterogeneity of each fractured section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fractured section.
Embodiments of the present application further provide a computer device, which includes a processor and a memory for storing processor-executable instructions, where the processor executes the instructions to implement the steps of the method for determining heterogeneity of a shale gas reservoir as described in any of the above embodiments.
Embodiments of the present application also provide a computer-readable storage medium having stored thereon computer instructions, which when executed, implement the steps of the method for determining heterogeneity of a shale gas reservoir as described in any of the above embodiments.
In the embodiment of the application, the method for determining the heterogeneity of the shale gas reservoir is provided, casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of the target shale gas reservoir in a preset time period can be obtained, and the heterogeneity range of the target shale gas reservoir which can be determined based on the hydraulic fracturing construction curves is more comprehensive due to the fact that the hydraulic fracturing construction curves can represent the heterogeneity of a far well reservoir. Performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; fourier transformation is carried out on the multiple eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, and the heterogeneity of each fracturing section of the target shale gas reservoir is determined according to the Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, so that the overall heterogeneity condition of the shale gas reservoir can be truly and accurately determined, and the target shale gas reservoir can be developed more efficiently.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, are incorporated in and constitute a part of this application, and are not intended to limit the application. In the drawings:
FIG. 1 is a schematic diagram illustrating steps of a method for determining heterogeneity of a shale gas reservoir provided by an embodiment of the present application;
FIG. 2 illustrates a schematic diagram of ideal fracture construction curve characteristics provided by an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating gentle stage casing pressure data of each fracture section in an actually measured fracture construction curve according to an embodiment of the present disclosure;
FIG. 4 illustrates an empirical mode decomposition of casing pressure data for the 7 th fracture zone provided by an embodiment of the present application;
FIG. 5 shows a Fourier energy spectrum of 9 eigenmode functions of a 7 th fracture zone provided by an embodiment of the present application;
FIG. 6 illustrates a log fit of the rank of each eigenmode function to the spectrally weighted average wavenumber of each eigenmode function for a 7 th fracture zone provided by an embodiment of the present application;
fig. 7 is a schematic structural diagram illustrating an apparatus for determining heterogeneity of a shale gas reservoir according to an embodiment of the present disclosure;
fig. 8 shows a schematic structural diagram of a computer device provided in an embodiment of the present application.
Detailed Description
The principles and spirit of the present application will be described with reference to a number of exemplary embodiments. It should be understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the present application, and are not intended to limit the scope of the present application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As will be appreciated by one skilled in the art, embodiments of the present application may be embodied as a system, apparatus, device, method or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
Considering that the existing shale gas reservoir heterogeneity evaluation method usually adopts a core sample with a small data scale or logging information with limited resolution, so that the heterogeneity evaluation is mostly concentrated on a near-well reservoir, the heterogeneity of a far-well reservoir which cannot be represented by experimental data or logging interpretation information cannot be effectively evaluated, and the evaluation range is limited, thereby the whole heterogeneity condition of the shale gas reservoir is difficult to truly and accurately reflect.
Based on the above problems, embodiments of the present invention provide a method for determining heterogeneity of shale gas reservoirs, and although the present application provides method operation steps or apparatus structures as shown in the following examples or figures, more or fewer operation steps or module units may be included in the method or apparatus based on conventional or non-inventive labor. In the case of steps or structures which do not logically have the necessary cause and effect relationship, the execution sequence of the steps or the module structure of the apparatus is not limited to the execution sequence or the module structure described in the embodiments and shown in the drawings of the present application. When the described method or module structure is applied in an actual device or end product, the method or module structure according to the embodiments or shown in the drawings can be executed sequentially or executed in parallel (for example, in a parallel processor or multi-thread processing environment, or even in a distributed processing environment).
Fig. 1 is a schematic diagram illustrating steps of a method for determining heterogeneity of a shale gas reservoir provided according to an embodiment of the present application, the method may include the following steps, as shown in fig. 1.
S101, casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of the target shale gas reservoir within a preset time period are obtained.
The parameters such as mineral components, brittleness, rock mechanical properties, ground stress and the like of the hydraulic fracture can be changed when the hydraulic fracture meets heterogeneous shale in the process of expanding the far-well shale gas reservoir, and the change is correspondingly mainly reflected in the change of casing pressure data of a hydraulic fracturing construction curve. Wherein, hydraulic fracturing is generally a casing perforation fracturing mode, and pressure data can be called casing pressure data. And because a staged fracturing mode is usually adopted when the horizontal well is subjected to hydraulic fracturing, casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing stages of a target shale gas reservoir within a preset time period can be obtained in advance.
S102, performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section.
Empirical mode decomposition can be performed on casing pressure data of each fracturing section respectively to obtain a plurality of eigenmode functions obtained by decomposition of each fracturing section and determine the number of the eigenmode functions obtained by decomposition of each fracturing section. In one embodiment, Empirical Mode Decomposition (EMD) may be performed on the casing pressure data of each fracture section in a relatively gentle stage, wherein the EMD is a signal analysis method that performs signal Decomposition according to the time scale features of the data itself without setting any basis function in advance. The empirical mode decomposition method can be theoretically applied to the decomposition of any type of signals, and has obvious advantages in processing non-stationary and non-linear data. Any signal is composed of several eigenmode functions, i.e. a signal may contain several eigenmode functions at any time, and if the eigenmode functions overlap, a composite signal is formed. The purpose of empirical mode decomposition is to obtain eigenmode functions. Empirical mode decomposition is carried out on casing pressure data of each of the plurality of fracturing sections, and a plurality of eigenmode functions corresponding to each of the plurality of fracturing sections can be obtained.
S103, carrying out Fourier transform on the plurality of eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
Fourier transformation can be carried out on the plurality of eigenmode functions of each fracturing section, and a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is obtained. Further, in some embodiments of the present application, fourier transform is performed on the multiple eigenmode functions of each fracture zone, so as to obtain a fourier spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture zone. Then, according to the fourier spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section, the fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section can be determined.
Specifically, the fourier spectrum and the fourier energy spectrum of each of the plurality of eigenmode functions of each split segment may be determined according to the following formulas:
Sn,m(ω)＝|An,m(ω)|2；
wherein, IMFn,m(t) is the eigenmode function, IMF, corresponding to the mth eigenmode function of the nth fracture zonen,m(ω) is IMFn,m(t) corresponding image function, An,m(ω) is the Fourier spectrum, S, corresponding to the mth eigenmode function of the nth fracture intervaln,mAnd (omega) is a Fourier energy spectrum corresponding to the mth eigenmode function of the nth fracturing section. Wherein N is 1,2, then，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone.
And S104, determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
After the fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section is determined, the heterogeneity of each fracturing section of the target shale gas reservoir can be determined according to the multiple fourier energy spectrums in each fracturing section, and therefore the overall heterogeneity condition of the target shale gas reservoir is determined.
According to the method in the embodiment, casing pressure data of the hydraulic fracturing construction curves of the plurality of fracturing sections of the target shale gas reservoir in the preset time period can be obtained, and the hydraulic fracturing construction curves can represent the heterogeneity of the far-well reservoir, so that the heterogeneity range of the target shale gas reservoir which can be determined based on the hydraulic fracturing construction curves is more comprehensive. Performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; fourier transformation is carried out on the multiple eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, and the heterogeneity of each fracturing section of the target shale gas reservoir is determined according to the Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, so that the overall heterogeneity condition of the shale gas reservoir can be truly and accurately determined, and the target shale gas reservoir can be developed more efficiently.
In some embodiments of the present application, determining the heterogeneity of each fractured segment of the target shale gas reservoir according to the fourier energy spectrum corresponding to each of the plurality of eigenmode functions of each fractured segment includes: determining a spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section; and determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
The spectral weighted average wave number corresponding to each eigenmode function of the plurality of eigenmode functions of each fracture section can be determined according to the Fourier energy spectrum corresponding to each eigenmode function of the plurality of eigenmode functions of each fracture section. After the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is determined, the heterogeneity of each fracturing section of the target shale gas reservoir can be determined according to the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section. Specifically, the heterogeneity may show that a distribution of a certain property parameter is uneven, the heterogeneity causes the stress wave to be prone to fluctuation when propagating in the shale, and the fluctuation causes the propagation period of the stress wave to be large and the frequency to be small. Since the frequency is in positive correlation with the spectrum weighted average wave number, the stronger the heterogeneity, the smaller the spectrum weighted average wave number, further resulting in the proportion of the smaller spectrum weighted average wave number being increased, thereby resulting in the smaller difference between the whole spectrum weighted average wave number and the slower change of the spectrum weighted average wave number. That is, the faster the spectrum weighted average wave number corresponding to each eigenmode function of each fracture section changes with the number of each eigenmode function, the weaker the heterogeneity, and the slower the spectrum weighted average wave number corresponding to each eigenmode function changes with the number of each eigenmode function, the stronger the heterogeneity. By the method, the heterogeneity condition of each fracturing section can be determined according to the spectrum weighted average wave number corresponding to each eigenmode function of each fracturing section.
Further, in some embodiments of the present application, determining a spectrally weighted average wave number for each of the plurality of eigenmode functions of each fracture zone based on the fourier energy spectrum for each of the plurality of eigenmode functions of each fracture zone comprises determining a spectrally weighted average wave number for each of the plurality of eigenmode functions of each fracture zone according to the following formula:
wherein k isn,mFor the spectral weighted average wavenumber, S, corresponding to the mth eigenmode function of the nth fracture zonen,m(k) A fourier energy spectrum corresponding to an mth eigenmode function of the nth fracturing stage, where N is 1,2n，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone. Where the period, wavenumber (equal to angular frequency) can be averaged by spectral weightingDivided by the wave velocity), the transform yields a spectrally weighted average wave number.
Further, in some embodiments of the present application, determining the heterogeneity of each fractured segment of the target shale gas reservoir according to the spectrally weighted average wavenumber corresponding to each eigenmode function of the plurality of eigenmode functions of each fractured segment includes: and fitting the spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section with the serial number of each eigenmode function in the plurality of eigenmode functions of each fracturing section to obtain a heterogeneous index, wherein the heterogeneous index is in negative correlation with the strength of non-homogeneity.
Specifically, the heterogeneous index may be obtained by fitting the spectrum weighted average wave number corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section with the sequence number of each eigenmode function in the multiple eigenmode functions of each fracture section according to the following formula:
log kn,m＝log kn0-m logρn；
wherein k isn,mFor the spectral weighted average wavenumber, k, corresponding to the mth eigenmode function of the nth fracture intervaln0Is a constant, rho, corresponding to the nth fracturing stagenAnd the heterogeneous index corresponding to the nth fracturing stage. Wherein N is 1,2, then，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone. Wherein the heterogeneous index is inversely related to the strength of the inhomogeneity. That is, the smaller the heterogeneity index is, the stronger the heterogeneity is; the larger the heterogeneity index, the weaker the heterogeneity. By the method, the heterogeneous index of each of the plurality of fractured segments in the target shale gas reservoir can be quantitatively and accurately determined, so that the overall heterogeneity of the target shale gas reservoir can be quantitatively evaluated.
In some embodiments of the present application, a starting point of the preset time period is a time point corresponding to ten percent reduction of the casing pressure data from the highest point in the hydraulic fracturing construction curve, and an ending point of the preset time period is a time point corresponding to reduction of the casing pressure data to the reservoir pressure in the hydraulic fracturing construction curve.
Specifically, in order to ensure that the obtained casing pressure data can well characterize the target shale gas reservoir, casing pressure data of a plurality of fracturing sections in a relatively gentle stage in an actually measured hydraulic fracturing construction curve can be obtained. The ideal hydraulic fracture construction curve includes: the method comprises a fracture initiation stage, an expansion stage (pad fluid and sand carrying fluid) and a pump stopping stage, so that a casing pressure curve of a relatively flat and slow stage in an actually measured hydraulic fracturing construction curve can be determined. Specifically, a time point when the casing pressure data is reduced from the highest point (representing a hydraulic fracture cracking point) of the hydraulic fracture construction curve to a time point when the relative variation range of the casing pressure data is within 10% can be used as a starting point of the preset time range, and a time point when the pump is stopped when the casing pressure data is rapidly reduced to a time point corresponding to the reservoir pressure can be used as an end point of the preset time range. And the casing pressure data in the preset time range is the casing pressure data of a plurality of fracturing sections in the actually measured hydraulic fracturing construction curve at relatively gentle stages.
In some embodiments of the present application, performing empirical mode decomposition based on casing pressure data of each of a plurality of fracture stages to obtain a plurality of eigenmode functions corresponding to each fracture stage, including: acquiring all maximum value points and minimum value points of the casing pressure data of the target fracturing section along with time change; fitting to form an upper envelope line by utilizing a cubic spline interpolation function based on all maximum value points of the casing pressure data of the target fracturing section along with time change; fitting by utilizing a cubic spline interpolation function to form a lower envelope line based on all minimum value points of the casing pressure data of the target fracturing section along with time change; determining the mean value of the upper envelope line and the lower envelope line based on the upper envelope line and the lower envelope line; determining casing pressure data residual error of the target fracturing section based on the mean value of the upper envelope line and the lower envelope line; determining whether the number of local zero points and zero points of casing pressure data residual errors of a target fracturing section is equal to or different from one point, and whether the mean value of an upper envelope line and a lower envelope line is 0; and under the condition that the local zero point and the zero point of the casing pressure data residual error of the target fracturing section are equal or different by one point and the mean value of the upper envelope line and the lower envelope line is 0, taking the casing pressure data residual error of the target fracturing section as an eigenmode function obtained by decomposition.
Consider that the empirical mode decomposition method is based on the following assumptions: the data includes at least two extrema, a maximum and a minimum; the local time domain characteristic of the data is uniquely determined by the time scale between extreme points; if the data has no extreme point but has an inflection point, the extreme value can be obtained by differentiating the data once or more times, and then the decomposition result can be obtained by integrating. The essence is to obtain the intrinsic fluctuation mode through the characteristic time scale of the data and then decompose the data. When empirical mode decomposition is respectively carried out on each fracturing section, all maximum value points and minimum value points of the casing pressure data of a target fracturing section in the plurality of fracturing sections, which change along with time, can be obtained in advance, an upper envelope line is formed by fitting of a cubic spline interpolation function on the basis of all maximum value points of the casing pressure data of the target fracturing section, which change along with time, and a lower envelope line is formed by fitting of the cubic spline interpolation function on the basis of all minimum value points of the casing pressure data of the target fracturing section, which change along with time. The cubic spline interpolation is a process of mathematically obtaining a curve function set by solving a three bending moment equation set through a smooth curve of a series of shape value points.
Further, a mean value of the upper envelope line and the lower envelope line may be determined based on the fitted upper envelope line and lower envelope line, and a difference value between the casing pressure data of the target fracture section and the mean value of the upper envelope line and the lower envelope line may be used as a casing pressure data residual of the target fracture section. In order to determine whether the decomposition is completed, it may be determined whether the number of local zero-points and zero-points of the casing pressure data residual of the target fracture section is equal to or different from one another, and whether the mean value of the upper envelope and the lower envelope is 0. When it is determined that the local zero-pole point and the zero-pole point of the casing pressure data residual of the target fracturing segment are equal to or different from each other by one, and the mean value of the upper envelope line and the lower envelope line is 0, the casing pressure data residual of the target fracturing segment is an eigenmode function, and the casing pressure data residual of the target fracturing segment can be used as an eigenmode function obtained by decomposition.
Specifically, under the condition that it is determined that the number of local zero poles of the casing pressure data residual of the target fracturing segment is not equal to or differs from one zero pole, and/or the mean value of the upper envelope and the lower envelope is not 0, it is indicated that the casing pressure data is not completely decomposed, fitting can be continuously performed by using a cubic spline interpolation function based on the casing pressure data residual of the target fracturing segment to obtain the upper envelope and the lower envelope, and the above operations are repeated based on the upper envelope and the lower envelope obtained by fitting until the number of local zero poles of the casing pressure data residual is equal to or differs from one zero pole, and the mean value of the upper envelope and the lower envelope is 0, and then the casing pressure data residual can be used as an eigenmode function obtained by decomposition.
After decomposing to obtain an eigenmode function, taking the difference between the casing pressure data of the target fracture section and the eigenmode function as new casing pressure data, continuing to perform fitting by using a cubic spline interpolation function to obtain an upper envelope line and a lower envelope line of the new casing pressure data, and repeating the above operations based on the upper envelope line and the lower envelope line of the new casing pressure data. And repeating the steps until the number of local zero poles and zero crossings of the obtained new casing pressure data is equal to or different from one another, and the mean value of the upper envelope line and the lower envelope line is 0, completing empirical mode decomposition, obtaining a plurality of eigenmode functions and determining the number of the eigenmode functions obtained by the decomposition of each fracturing section.
The above method is described below with reference to a specific example, however, it should be noted that the specific example is only for better describing the present application and is not to be construed as limiting the present application.
The invention provides a method for determining heterogeneity of a shale gas reservoir, which comprises the following steps:
The casing pressure of a gentle stage in the actual measurement hydraulic fracturing construction curve can be selected according to the characteristics of the ideal fracturing construction curveData, ideal fracture construction curves include: the fracture initiation, propagation (pad, sand) and pump-down stages, the ideal fracture construction curve characteristics may be as shown in fig. 2, where t1To t2Between the two stages is a hydraulic fracture propagation stage. Taking a fracturing curve of hydraulic fracturing construction of a certain shale gas well in the Wenquan area of the Sichuan basin as an example, sleeve pressure data of a sleeve pressure slow stage in an actually measured fracturing construction curve is selected and recorded as Pn(t), where N denotes the nth fracturing stage, N1, 2.. wherein N is the number of the plurality of fracturing stages of the shale gas reservoir, and t denotes the fracturing time, wherein the flat stage casing pressure data of each fracturing stage in the measured fracturing construction curve may include 11 fracturing stages in total as shown in fig. 3.
And 2, performing empirical mode decomposition on casing pressure data of relatively gentle stages of each selected fracturing section in the plurality of fracturing sections.
Empirical mode decomposition is a signal analysis method. The signal decomposition is carried out according to the time scale characteristics of the data, and any basis function is not required to be preset. The empirical mode decomposition method can be theoretically applied to the decomposition of any type of signals, and has obvious advantages in processing non-stationary and non-linear data. The empirical mode decomposition is carried out on casing pressure data of relatively gentle stages of all fracturing sections in a hydraulic fracturing construction curve, wherein the empirical mode decomposition comprises the following steps:
step 2.1: determining casing pressure data Pn(t) fitting all maximum value points and minimum value points which change along with the time t by using a cubic spline interpolation function to form an upper envelope line and a lower envelope line respectively. And the mean of the upper and lower envelope is taken as the
Then, there are:
wherein the content of the first and second substances,
is n thThe first casing pressure data residual of each fracture section.
Step 2.2: persistence versus residual data
Decomposing until
The method meets the requirement that the number of local zero poles and zero-crossing points is equal or different by one in all time, and the decomposition is stopped when the average value of local upper and lower envelopes is zero at any moment, at the moment, the records are carried out
IMFn,mAnd decomposing the casing pressure data of the nth fracturing section to obtain the mth eigenmode function.
Step 2.3: will Pn(t)-IMFn,iRepeating step 2.1 and step 2.2 as new casing pressure data to obtain all MnAn eigenmode function, where M1, 2n. As shown in fig. 4, which is an empirical mode decomposition diagram of the casing pressure data of the 7 th fracture zone, the casing pressure data of the 7 th fracture zone is decomposed into 9 eigenmode functions including IMF1-IMF9, and the last remainder is denoted as result, where the ordinate is the amplitude.
And 3, carrying out Fourier transform on the plurality of eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section. Specifically, fourier transform is performed on the multiple eigenmode functions of each fracture zone, and a fourier spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture zone can be obtained. Then, according to the fourier spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section, the fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section can be determined. The fourier spectrum and the fourier energy spectrum of each of the plurality of eigenmode functions of each split segment may be determined according to the following equations:
Sn,m(ω)＝|An,m(ω)|2；
wherein, IMFn,m(t) is the eigenmode function, IMF, corresponding to the mth eigenmode function of the nth fracture zonen,m(ω) is IMFn,m(t) corresponding image function, An,m(ω) is the Fourier spectrum, S, corresponding to the mth eigenmode function of the nth fracture intervaln,mAnd (omega) is a Fourier energy spectrum corresponding to the mth eigenmode function of the nth fracturing section. Wherein N is 1,2, then，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone. Referring to fig. 5, a fourier energy spectrum of the 9 eigenmode functions of the 7 th fracture zone is shown, as shown in fig. 5.
And 4, determining the average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section. Specifically, the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracture zone is determined according to the following formula:
wherein k isn,mFor the spectral weighted average wavenumber, S, corresponding to the mth eigenmode function of the nth fracture zonen,m(k) A fourier energy spectrum corresponding to an mth eigenmode function of the nth fracturing stage, where N is 1,2n，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone.
And 5, fitting the average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section with the serial number of each eigenmode function in the plurality of eigenmode functions of each fracturing section to obtain a heterogeneous index, wherein the heterogeneous index is in negative correlation with the strength of non-homogeneity. As shown in fig. 6, a log fit plot of the index number of each eigenmode function to the average wave number of each eigenmode function for the 7 th fracture zone is shown. In fig. 6, the horizontal axis represents the number m of eigenmode functions, and the vertical axis represents the logarithm of the average wave number of each eigenmode function, and the fitting is performed according to the following equation:
log kn,m＝log kn0-m logρn；
wherein k isn,mFor the spectral weighted average wavenumber, k, corresponding to the mth eigenmode function of the nth fracture intervaln0Is a constant, rho, corresponding to the nth fracturing stagenAnd the heterogeneous index corresponding to the nth fracturing stage. Wherein N is 1,2, then，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone. Wherein the heterogeneous index is inversely related to the strength of the inhomogeneity. That is, the smaller the heterogeneity index is, the stronger the heterogeneity is; the larger the heterogeneity index, the weaker the heterogeneity. As shown in fig. 6, the intercept log k of the 7 th fracture zone707.96228 ± 0.24262, slope-log ρ7-0.8177 ± 0.04311, R squared (COD) ═ 0.98091. Wherein, R square (COD) is the goodness of fit, the maximum value is 1, the closer the value is to 1, the better the fitting degree of the regression line is.
According to the method in the embodiment, the gentle stage in the casing pressure data of the actually measured fracturing construction curve is characterized as a hydraulic fracture expansion stage in a far-well reservoir, the casing pressure data of different fracturing sections are subjected to empirical mode decomposition to obtain each intrinsic mode function, the frequency spectrum of each intrinsic mode function is obtained after Fourier transform to obtain an energy spectrogram, the spectral weighted average wave number is obtained through calculation, finally, the serial number of each intrinsic mode function and the spectral weighted average wave number of each intrinsic mode function are fitted to obtain the heterogeneity index, the heterogeneity index of each fracturing section in a plurality of fracturing sections in the target shale gas reservoir can be quantitatively and accurately determined, and therefore the overall heterogeneity of the target shale gas reservoir can be quantitatively evaluated. Because the data based on the evaluation of the heterogeneity is real-time data of fracturing construction instead of logging data with limited resolution or core samples with smaller dimensions, compared with the prior art, the determined heterogeneity result of the shale gas reservoir in the far well is more real and accurate, the heterogeneity range of the target shale gas reservoir can be more comprehensive, and the overall heterogeneity condition of the shale gas reservoir can be quantitatively evaluated, so that the shale gas reservoir can be more efficiently developed based on the heterogeneity result of the shale gas reservoir in the far well.
Based on the same inventive concept, the embodiment of the present application further provides an apparatus for determining the heterogeneity of a shale gas reservoir, as described in the following embodiments. Because the principle of solving the problem of the device for determining the heterogeneity of the shale gas reservoir is similar to that of the method for determining the heterogeneity of the shale gas reservoir, the implementation of the device for determining the heterogeneity of the shale gas reservoir can refer to the implementation of the method for determining the heterogeneity of the shale gas reservoir, and repeated parts are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated. Fig. 7 is a block diagram of an apparatus for determining heterogeneity of shale gas reservoirs according to an embodiment of the present disclosure, as shown in fig. 7, including: an obtaining module 701, a decomposing module 702, a transforming module 703 and a determining module 704, the structure of which is described below.
The obtaining module 701 is configured to obtain casing pressure data of hydraulic fracturing construction curves of multiple fracturing stages of a target shale gas reservoir within a preset time period.
The decomposition module 702 is configured to perform empirical mode decomposition based on casing pressure data of each of the plurality of fracture sections to obtain a plurality of eigenmode functions corresponding to each of the fracture sections.
The transform module 703 is configured to perform fourier transform on the multiple eigenmode functions of each fracture section to obtain a fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracture section.
The determining module 704 is configured to determine the heterogeneity of each fractured segment of the target shale gas reservoir according to the fourier energy spectrum corresponding to each eigenmode function of the plurality of eigenmode functions of each fractured segment.
In some embodiments of the present application, the determining module may be specifically configured to: determining a spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section; and determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
In some embodiments of the present application, a starting point of the preset time period is a time point corresponding to ten percent reduction of the casing pressure data from the highest point in the hydraulic fracturing construction curve, and an ending point of the preset time period is a time point corresponding to reduction of the casing pressure data to the reservoir pressure in the hydraulic fracturing construction curve.
In some embodiments of the present application, the decomposition module may be specifically configured to: acquiring all maximum value points and minimum value points of the casing pressure data of the target fracturing section along with time change; fitting to form an upper envelope line by utilizing a cubic spline interpolation function based on all maximum value points of the casing pressure data of the target fracturing section along with time change; fitting by utilizing a cubic spline interpolation function to form a lower envelope line based on all minimum value points of the casing pressure data of the target fracturing section along with time change; determining the mean value of the upper envelope line and the lower envelope line based on the upper envelope line and the lower envelope line; determining casing pressure data residual error of the target fracturing section based on the mean value of the upper envelope line and the lower envelope line; determining whether the number of local zero points and zero points of casing pressure data residual errors of a target fracturing section is equal to or different from one point, and whether the mean value of an upper envelope line and a lower envelope line is 0; and under the condition that the local zero point and the zero point of the casing pressure data residual error of the target fracturing section are equal or different by one point and the mean value of the upper envelope line and the lower envelope line is 0, taking the casing pressure data residual error of the target fracturing section as an eigenmode function obtained by decomposition.
In some embodiments of the present application, the transformation module may be specifically configured to: fourier transformation is carried out on the plurality of eigenmode functions of each fracturing section, and a Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section is obtained; and determining a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
In some embodiments of the present application, determining a spectrally weighted average wave number for each of the plurality of eigenmode functions of each fracture zone based on the fourier energy spectrum for each of the plurality of eigenmode functions of each fracture zone comprises determining a spectrally weighted average wave number for each of the plurality of eigenmode functions of each fracture zone according to the following equation:
wherein k isn,mFor the spectral weighted average wavenumber, S, corresponding to the mth eigenmode function of the nth fracture zonen,m(k) A fourier energy spectrum corresponding to an mth eigenmode function of the nth fracturing stage, where N is 1,2n，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone.
In some embodiments of the present application, determining the heterogeneity of each fractured segment of the target shale gas reservoir according to the spectrally weighted average wavenumber corresponding to each eigenmode function of the plurality of eigenmode functions of each fractured segment includes: and fitting the spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section with the serial number of each eigenmode function in the plurality of eigenmode functions of each fracturing section to obtain a heterogeneous index, wherein the heterogeneous index is in negative correlation with the strength of non-homogeneity.
From the above description, it can be seen that the embodiments of the present application achieve the following technical effects: casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period can be obtained, and the hydraulic fracturing construction curves can represent the heterogeneity of a far-well reservoir, so that the heterogeneity range of the target shale gas reservoir which can be determined based on the hydraulic fracturing construction curves is more comprehensive. Performing empirical mode decomposition on the basis of casing pressure data of each fracturing section in the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section; fourier transformation is carried out on the multiple eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, and the heterogeneity of each fracturing section of the target shale gas reservoir is determined according to the Fourier energy spectrum corresponding to each eigenmode function in the multiple eigenmode functions of each fracturing section, so that the overall heterogeneity condition of the shale gas reservoir can be truly and accurately determined, and the target shale gas reservoir can be developed more efficiently.
The embodiment of the present application further provides a computer device, which may specifically refer to a schematic structural diagram of the computer device shown in fig. 8 based on the method for determining the heterogeneity of the shale gas reservoir provided in the embodiment of the present application, where the computer device may specifically include an input device 81, a processor 82, and a memory 83. Wherein the memory 83 is configured to store processor-executable instructions. The processor 82 when executing the instructions performs the steps of the method for determining shale gas reservoir heterogeneity as described in any of the embodiments above.
In this embodiment, the input device may be one of the main apparatuses for information exchange between a user and a computer system. The input device may include a keyboard, a mouse, a camera, a scanner, a light pen, a handwriting input board, a voice input device, etc.; the input device is used to input raw data and a program for processing the data into the computer. The input device can also acquire and receive data transmitted by other modules, units and devices. The processor may be implemented in any suitable way. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The memory may in particular be a memory device used in modern information technology for storing information. The memory may include multiple levels, and in a digital system, the memory may be any memory as long as it can store binary data; in an integrated circuit, a circuit without a physical form and with a storage function is also called a memory, such as a RAM, a FIFO and the like; in the system, the storage device in physical form is also called a memory, such as a memory bank, a TF card and the like.
In this embodiment, the functions and effects of the specific implementation of the computer device can be explained in comparison with other embodiments, and are not described herein again.
There is also provided in an embodiment of the present application a computer storage medium based on the method for determining shale gas reservoir heterogeneity, where the computer storage medium stores computer program instructions that, when executed, implement the steps of the method for determining shale gas reservoir heterogeneity described in any of the above embodiments.
In the present embodiment, the storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard disk (HDD), or a Memory Card (Memory Card). The memory may be used to store computer program instructions. The network communication unit may be an interface for performing network connection communication, which is set in accordance with a standard prescribed by a communication protocol.
In this embodiment, the functions and effects specifically realized by the program instructions stored in the computer storage medium can be explained by comparing with other embodiments, and are not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the present application described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different from that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
It is to be understood that the above description is intended to be illustrative, and not restrictive. Many embodiments and many applications other than the examples provided will be apparent to those of skill in the art upon reading the above description. The scope of the application should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the pending claims along with the full scope of equivalents to which such claims are entitled.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and it will be apparent to those skilled in the art that various modifications and variations can be made in the embodiment of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method of determining shale gas reservoir heterogeneity, comprising:
acquiring casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period;
performing empirical mode decomposition on the basis of casing pressure data of each of the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section;
performing Fourier transform on the plurality of eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section;
and determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
2. The method of claim 1, wherein determining the heterogeneity of each fractured segment of the target shale gas reservoir based on the fourier energy spectrum corresponding to each of the plurality of eigenmode functions of each fractured segment comprises:
determining a spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section;
and determining the heterogeneity of each fracturing section of the target shale gas reservoir according to the spectral weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
3. The method of claim 1, wherein a starting point of the preset time period is a time point corresponding to ten percent reduction of the casing pressure data from a highest point in the hydraulic fracturing construction curve, and an end point of the preset time period is a time point corresponding to reduction of the casing pressure data to a reservoir pressure in the hydraulic fracturing construction curve.
4. The method of claim 1, wherein performing empirical mode decomposition based on casing pressure data of each of the plurality of fracture sections to obtain a plurality of eigenmode functions corresponding to each of the plurality of fracture sections comprises:
acquiring all maximum value points and minimum value points of the casing pressure data of the target fracturing section along with time change;
fitting by utilizing a cubic spline interpolation function to form an upper envelope line based on all maximum value points of the casing pressure data of the target fracturing section along with time change;
fitting by utilizing a cubic spline interpolation function to form a lower envelope line based on all minimum value points of the casing pressure data of the target fracturing section along with time change;
determining a mean of the upper envelope and the lower envelope based on the upper envelope and the lower envelope;
determining casing pressure data residual error of the target fracturing segment based on the mean value of the upper envelope line and the lower envelope line;
determining whether the number of local zero points and zero points of casing pressure data residual errors of the target fracturing section is equal to or different from one point, and whether the mean value of the upper envelope line and the lower envelope line is 0;
and under the condition that the number of local zero points and zero points of the casing pressure data residual error of the target fracturing segment is equal to or different from one point, and the mean value of the upper envelope line and the lower envelope line is 0, taking the casing pressure data residual error of the target fracturing segment as an eigenmode function obtained by decomposition.
5. The method of claim 1, wherein fourier transforming the plurality of eigenmode functions of each fracture zone to obtain a fourier energy spectrum corresponding to each of the plurality of eigenmode functions of each fracture zone comprises:
performing Fourier transform on the plurality of eigenmode functions of each fracturing section to obtain a Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section;
and determining a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section according to the Fourier spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section.
6. The method of claim 2, wherein determining the spectrally weighted average wave number for each of the plurality of eigenmode functions for each fracture zone based on the fourier energy spectrum for each of the plurality of eigenmode functions for each fracture zone comprises determining the spectrally weighted average wave number for each of the plurality of eigenmode functions for each fracture zone according to the following equation:
wherein k isn,mIs the mth book of the nth fracturing stageSpectral weighted average wavenumber, S, corresponding to the eigenmode functionn,m(k) A fourier energy spectrum corresponding to an mth eigenmode function of the nth fracturing stage, where N is 1,2n，MnThe number of the plurality of eigenmode functions corresponding to the nth fracture zone.
7. The method of claim 1, wherein determining the heterogeneity of each fractured segment of the target shale gas reservoir based on the spectrally weighted average wavenumber corresponding to each of the plurality of eigenmode functions of each fractured segment comprises:
and fitting the spectrum weighted average wave number corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section with the serial number of each eigenmode function in the plurality of eigenmode functions of each fracturing section to obtain a heterogeneous index, wherein the heterogeneous index is in negative correlation with the strength of non-homogeneity.
8. An apparatus for determining heterogeneity of a shale gas reservoir, comprising:
the acquisition module is used for acquiring casing pressure data of hydraulic fracturing construction curves of a plurality of fracturing sections of a target shale gas reservoir within a preset time period;
the decomposition module is used for carrying out empirical mode decomposition on the basis of casing pressure data of each of the plurality of fracturing sections to obtain a plurality of eigenmode functions corresponding to each fracturing section;
the transformation module is used for carrying out Fourier transformation on the plurality of eigenmode functions of each fracturing section to obtain a Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fracturing section;
and the determining module is used for determining the heterogeneity of each fractured section of the target shale gas reservoir according to the Fourier energy spectrum corresponding to each eigenmode function in the plurality of eigenmode functions of each fractured section.
9. A computer device comprising a processor and a memory for storing processor-executable instructions which, when executed by the processor, implement the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium having computer instructions stored thereon which, when executed, implement the steps of the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010181237.XA CN111208580A (en) | 2020-03-16 | 2020-03-16 | Method and device for determining heterogeneity of shale gas reservoir |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010181237.XA CN111208580A (en) | 2020-03-16 | 2020-03-16 | Method and device for determining heterogeneity of shale gas reservoir |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111208580A true CN111208580A (en) | 2020-05-29 |
Family
ID=70789972
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010181237.XA Pending CN111208580A (en) | 2020-03-16 | 2020-03-16 | Method and device for determining heterogeneity of shale gas reservoir |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111208580A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835101A (en) * | 2021-03-13 | 2021-05-25 | 中国石油大学(华东) | Fracture fluid factor prediction method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2563323C1 (en) * | 2014-04-02 | 2015-09-20 | Открытое акционерное общество "Нефтяная компания "Роснефть" | Method of reconstruction of fine structure of geological object and forecast of its fluid saturation |
| CN110096673A (en) * | 2019-04-29 | 2019-08-06 | 河北工业大学 | A kind of EMD improved method suitable for signal decomposition |
| CN110485994A (en) * | 2019-08-20 | 2019-11-22 | 中国石油大学(北京) | The determination method, apparatus and equipment of shale gas reservoir heterogeneity |
-
2020
- 2020-03-16 CN CN202010181237.XA patent/CN111208580A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2563323C1 (en) * | 2014-04-02 | 2015-09-20 | Открытое акционерное общество "Нефтяная компания "Роснефть" | Method of reconstruction of fine structure of geological object and forecast of its fluid saturation |
| CN110096673A (en) * | 2019-04-29 | 2019-08-06 | 河北工业大学 | A kind of EMD improved method suitable for signal decomposition |
| CN110485994A (en) * | 2019-08-20 | 2019-11-22 | 中国石油大学(北京) | The determination method, apparatus and equipment of shale gas reservoir heterogeneity |
Non-Patent Citations (2)
| Title |
|---|
| WENBAO ZHAI 等: "Heterogeneity analysis of shale reservoir based on multi-stage pumping data", 《OPEN GEOSCIENCES》 * |
| 程鹏飞 等: "《国家大地坐标系建立的理论与实践》", 31 December 2016 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835101A (en) * | 2021-03-13 | 2021-05-25 | 中国石油大学(华东) | Fracture fluid factor prediction method and system |
| CN112835101B (en) * | 2021-03-13 | 2022-04-15 | 中国石油大学(华东) | Fracture fluid factor prediction method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109209321B (en) | Fracturing potential-based horizontal well fracturing design method and device to be fractured | |
| US20210350208A1 (en) | Method and device for predicting production performance of oil reservoir | |
| RU2669948C2 (en) | Multistage oil field design optimisation under uncertainty | |
| CN111425193B (en) | Reservoir compressibility evaluation method based on clustering analysis logging rock physical facies division | |
| CN109490963B (en) | Fractured reservoir rock physical modeling method and system | |
| AU2019340410B2 (en) | Reservoir characterization utilizing inversion of resampled seismic data | |
| CN113919219A (en) | Stratum evaluation method and system based on logging big data | |
| CN108375785B (en) | Method and device for correcting position of crack belt | |
| CN109655903A (en) | Rammell S-Wave Velocity Predicted Method and system | |
| CN111751877A (en) | Seismic data multiple-integration coherent fracture prediction method and device | |
| CN111999163A (en) | Method and device for evaluating rock brittleness | |
| CN111208580A (en) | Method and device for determining heterogeneity of shale gas reservoir | |
| CN110485994B (en) | Method, device and equipment for determining heterogeneity of shale gas reservoir | |
| CN111781662B (en) | Reservoir fracture parameter obtaining method, device and equipment | |
| CN112987088A (en) | Seepage medium seismic transverse wave numerical simulation and imaging method | |
| Wang et al. | Improvement of autoregressive model-based algorithms for picking the arrival times of the P-wave of rock acoustic emission | |
| Forristall | Joint wave height and period statistics from linear simulations | |
| CN113153259A (en) | Method, device, equipment and storage medium for determining mineral components of carbonate rock | |
| Flatté et al. | Comparison between ocean-acoustic fluctuations in parabolic-equation simulations and estimates from integral approximations | |
| Martemyanov et al. | Analytic modelling for wellbore stability analysis | |
| Xu et al. | Frequency trend attribute analysis for stratigraphic division and correlation | |
| Wang et al. | Machine learning–informed soil conditioning for mechanized shield tunneling | |
| CN112836163A (en) | Diagenetic logging quantitative division method, device and equipment | |
| CN117077446B (en) | Unconventional reservoir comprehensive brittleness index evaluation method and application system | |
| CN107871028A (en) | A kind of partition of the level method and device of SEQUENCE STRATIGRAPHIC |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200529 |