CN111077574A - Method, device and system for determining stratum elastic parameters - Google Patents
Method, device and system for determining stratum elastic parameters Download PDFInfo
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/282—Application of seismic models, synthetic seismograms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
Abstract
The embodiment of the specification discloses a method, a device and a system for determining stratum elastic parameters, wherein the method comprises the steps of obtaining actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of a target work area; obtaining a target function for representing the approximate relation between actually-measured seismic data and theoretical seismic data calculated based on elastic parameters, wherein the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters comprise reservoir parameters and fluid parameters; and performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area. By utilizing the embodiments of the specification, the accuracy of obtaining the elastic parameters by inversion can be greatly improved.
Description
Technical Field
The invention relates to the technical field of seismic exploration processing, in particular to a method, a device and a system for determining stratum elasticity parameters.
Background
Seismic reservoir and fluid identification specifically refers to the process of detecting and describing subsurface reservoirs and fluids within the reservoirs through information carried by the seismic data. The elastic parameters extracted from the seismic data contain abundant information helpful for revealing the characteristics of the underground geologic body and the pore fluid in the reservoir. With the increasing difficulty of exploration and the progress of exploration technology, the lithology of underground rock strata and the identification of pore fluid based on elastic parameters become key technologies of oil and gas exploration at present. The method utilizes seismic information to carry out identification research on the properties of reservoirs and filling fluids in pores of the reservoirs, and needs to combine with rock physics theory to find a characterization means capable of highlighting the reservoirs and the fluids, and then further comprehensively predicts and describes the reservoir and the fluids. On the basis of high-quality seismic data, the accuracy of underground reservoir and pore fluid identification mainly depends on the sensitivity degree of selected characterization parameters to reservoirs or fluids and the reliability of a method for extracting relevant characterization parameters. Comprehensive analysis of elastic parameters is an effective way to explore the characteristics of underground reservoirs and pore fluids and qualitatively and quantitatively describe the condition of underground rock formations.
Researchers at home and abroad have also made a great deal of research on reservoir and fluid detection based on elastic parameters. Wherein Russell and the like combine the pore elasticity theory to provide a novel fluid factor PfluidAnd can be used for directly identifying the type of the fluid. The shear modulus mu represents the characteristics of a reservoir framework, can be used for describing the lithology characteristics of rocks, the density rho can also display the lithology characteristics of the reservoir, and Goodway et al illustrate the product mu rho ═ P of the tworeservoirThe method has better performance in the aspect of identifying the lithology of the reservoir. And currently extracts the parameter Pfluid、PreservoirThe method basically depends on a longitudinal wave inversion indirect calculation method, so that the accuracy of parameter extraction is limited.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide a method, an apparatus, and a system for determining an elastic parameter of a formation, which can greatly improve accuracy of obtaining the elastic parameter by inversion.
The specification provides a method, a device and a system for determining a stratum elasticity parameter, which are realized by the following modes:
a method of determining an elastic parameter of a formation, comprising:
acquiring actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of a target work area;
obtaining a target function for representing the approximate relation between actually-measured seismic data and theoretical seismic data calculated based on elastic parameters, wherein the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters comprise reservoir parameters and fluid parameters;
and performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area.
In another embodiment of the method described in this specification, the compressional wave approximation model includes:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Is the density parameter of the lower medium; rfluidAs rate of change of fluid parameter, L1Is a lower layerFluid parameter of the medium, L2Is the fluid parameter, k, of the underlying medium1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
In another embodiment of the method described herein, the converted wave approximation model comprises:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
In another embodiment of the method described herein, the objective function comprises:
wherein r represents longitudinal wave data determined according to a longitudinal wave approximation model; s represents converted wave data determined from a converted wave approximation model, W1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1A matrix consisting of wavelets for a longitudinal-wavelength-component angle superimposed data volume, C2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; Ω is a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is a low-frequency factor, and Gm is a low-frequency component of a reservoir parameter, a fluid parameter and a density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
In another embodiment of the method described in this specification, the performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the objective function to obtain elastic parameter data of the target work area includes:
performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data according to the target function to obtain a reservoir parameter change rate and a fluid parameter change rate;
and integrating the change rate of the reservoir parameters and the change rate of the fluid parameters to obtain the reservoir parameters and the fluid parameters.
In another aspect, an embodiment of the present specification further provides an apparatus for determining an elastic parameter of a formation, including:
the data acquisition module is used for acquiring actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of a target work area;
the inversion function acquisition module is used for acquiring a target function for representing the approximate relationship between the actually measured seismic data and theoretical seismic data calculated based on elastic parameters, the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters comprise reservoir parameters and fluid parameters;
and the inversion module is used for performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area.
In another embodiment of the apparatus described in this specification, the compressional wave approximation model includes:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Being the underlying mediumA density parameter; rfluidAs rate of change of fluid parameter, L1Is the fluid parameter of the underlying medium, L2Is the fluid parameter, k, of the underlying medium1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
In another embodiment of the apparatus described herein, the converted wave approximation model comprises:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
In another embodiment of the apparatus described herein, the objective function includes:
wherein r represents longitudinal wave data determined according to a longitudinal wave approximation model; s represents converted wave data determined from a converted wave approximation model, W1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1A matrix consisting of wavelets for a longitudinal-wavelength-component angle superimposed data volume, C2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; Ω is a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is a low-frequency factor, and Gm is a low-frequency component of a reservoir parameter, a fluid parameter and a density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
In another aspect, the present description further provides a system for determining a formation elasticity parameter, the system including at least one processor and a memory storing computer-executable instructions, the processor implementing the steps of the method according to any one of the above embodiments when executing the instructions.
According to the method, the device and the system for determining the elastic parameters of the stratum, which are provided by one or more embodiments of the specification, the elastic parameters representing the reservoir and the fluid can be directly calculated on the basis of the sub-angle superposition data body by using the inversion model directly representing the distribution characteristics of the reservoir parameters and the fluid parameters, indirect calculation is not needed, and the accumulated error introduced by the indirect calculation is reduced. And the converted wave information is added in the inversion process, so that the accuracy of the inversion result is greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort. In the drawings:
FIG. 1 is a schematic flow chart diagram illustrating one embodiment of a method for determining an elastic parameter of a formation as provided herein;
FIG. 2 is a flow chart illustrating a method for determining an elasticity parameter according to an embodiment provided herein;
FIG. 3 is a graph illustrating sensitivity to different fluid indicators in another embodiment provided herein;
FIG. 4 is a schematic diagram of inversion test theory data and an initial model in another embodiment provided herein;
FIG. 5 is a schematic illustration of an noiseless corner gather in another embodiment provided herein;
FIG. 6 is a schematic illustration of a noisy angle gather in another embodiment provided herein;
FIG. 7 is a schematic representation of inversion results of reservoir parameters and fluid parameters in another embodiment provided herein;
FIG. 8 is a schematic representation of inversion results of reservoir parameters and fluid parameters in another embodiment provided herein;
FIG. 9 is a schematic representation of inversion results of reservoir parameters and fluid parameters in another embodiment provided herein;
fig. 10 is a schematic block diagram of an embodiment of an apparatus for determining an elastic parameter of a formation provided in the present specification.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the drawings in one or more embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the specification, and not all embodiments. All other embodiments obtained by a person skilled in the art based on one or more embodiments of the present specification without making any creative effort shall fall within the protection scope of the embodiments of the present specification.
FIG. 1 is a schematic flow chart of an embodiment of the method for determining an elastic parameter of a formation provided herein. Although the present specification provides the method steps or apparatus structures as shown in the following examples or figures, more or less steps or modules may be included in the method or apparatus structures based on conventional or non-inventive efforts. In the case of steps or structures which do not logically have the necessary cause and effect relationship, the execution order of the steps or the block structure of the apparatus is not limited to the execution order or the block structure shown in the embodiments or the drawings of the present specification. When the described method or module structure is applied to a device, a server or an end product in practice, the method or module structure according to the embodiment or the figures may be executed sequentially or in parallel (for example, in a parallel processor or multi-thread processing environment, or even in an implementation environment including distributed processing and server clustering).
In one embodiment of the method for determining an elastic parameter of a formation provided herein, as shown in fig. 1, the method may be applied to a processing apparatus for performing an inversion process of an elastic parameter of a formation, and the method may include:
s20: and acquiring the actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of the target work area.
The processing device may obtain longitudinal wavelength division angle seismic data and converted wavelength division angle seismic data for a target work area. If the method can obtain the actually measured longitudinal wave prestack seismic data and converted wave prestack seismic data of the target work area, the seismic data is subjected to optimization processing including amplitude compensation processing, energy compensation and equalization processing, regularization and the like, noise removal, multiple wave removal, high resolution, full three-dimensional denoising, gather leveling and the like. And performing angle-division stacking on the pre-stack seismic data after the optimization processing to obtain the actual measurement longitudinal wave-division angle seismic data and the converted wave-division angle seismic data of the target work area.
The method includes the steps of calculating theoretical angle gather data of a target interval by utilizing logging data, calculating an amplitude versus incidence Angle (AVO) curve of the theoretical gather in the target interval, calculating an AVO curve value of an actual seismic gather at a well point position, carrying out correlation analysis on the AVO curve of a synthetic gather and the AVO curve of the actual seismic gather, determining an angle range with high correlation as an effective angle, and analyzing the effective incidence angle αi(i-1, 2.. M) are equally divided into M pieces of angle division data in sequence, wherein M is greater than or equal to 3. Then, the data are respectively superposed to obtain M longitudinal wave division angle superposition data volumes (r)1,r2...rM) And M converted wavelength division angle superimposed data volumes(s)1,s2...sM)。
In other embodiments, the longitudinal wave seismic wavelets and the converted wave seismic wavelets may be extracted according to the longitudinal wave division angle seismic data and the converted wave division angle seismic data, respectively. The processing equipment can acquire the actually measured longitudinal wave component angle seismic data and the converted wave component angle seismic data of the target work area, and respectively extract longitudinal wave seismic wavelets and converted wave seismic wavelets according to the longitudinal wave component angle seismic data and the converted wave component angle seismic data.
For example, a borehole-side compressional seismic gather may be created using log data, based on the compressional seismic gather and the observed compressional angle superpositionEstimating the corresponding wavelet (omega) of each longitudinal wavelength division angle superposition data volume according to the volumep1,ωp2...ωpM). Utilizing logging data to make a well-side converted transverse wave synthetic seismic gather, and estimating a wavelet (omega) corresponding to each converted transverse wave angle superimposed data body based on the converted transverse wave synthetic seismic gather and the converted transverse wave angle superimposed data bodies obtained by observations1,ωs2...ωsM)。
S22: and obtaining a target function for representing the approximate relation between the actually measured seismic data and theoretical seismic data calculated based on the elastic parameters, wherein the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics.
The processing device may obtain an objective function that may represent a proximity relationship between the measured seismic data and theoretical seismic data calculated from the elastic parameters. The proximity relationship may refer to a difference between the measured seismic data and the theoretical seismic data calculated according to the elastic parameter, and the smaller the difference is, the closer the two data are.
In some embodiments, the objective function may be constructed from a compressional wave approximation model and a converted wave approximation model. The longitudinal wave approximation model and the converted wave approximation model can be a longitudinal wave data inversion model and a converted wave data inversion model used for indicating reservoir parameters and fluid parameter distribution characteristics, and the longitudinal wave approximation model and the converted wave approximation model can be constructed according to rock physical relations.
In some embodiments, the constructed compressional wave approximation model may include:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Is the density parameter of the lower medium; rfluidAs rate of change of fluid parameter, L1Is the fluid parameter of the underlying medium, L2Is the fluid parameter of the underlying medium, L1、L2Can be determined from the product of Gassmann fluid parameter and density, k1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
In some embodiments, the converted wave approximation model constructed may include:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
Then, an objective function can be constructed by utilizing the logging data, the common reflection point seismic gather and the longitudinal wave approximation model and the converted wave approximation model. In some embodiments, the objective function may be expressed as:
in the above formula, r represents longitudinal wave data and can be determined from the longitudinal wave approximation model; s represents converted wave data, which can be determined according to the converted wave approximation model; w1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1An integral matrix corresponding to the longitudinal wave data, C2An integral matrix corresponding to the converted wave data; omegajIs a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is lowThe frequency factor Gm is the low-frequency component of the reservoir parameter, the fluid parameter and the density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
S24: and performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area.
The longitudinal wave component angle seismic data and the converted wave component angle seismic data can be substituted into the objective function, the minimum value of the objective function is solved, and the elastic parameter data of the target work area are obtained. In some embodiments, inversion processing may be performed on the longitudinal wavelength division angle seismic data and the converted wavelength division angle seismic data according to the objective function to obtain a reservoir parameter change rate and a fluid parameter change rate; and integrating the change rate of the reservoir parameters and the change rate of the fluid parameters to obtain the reservoir parameters and the fluid parameters.
The change rate parameter integral can be obtained on the basis of the initial model to obtain the elastic parameters for representing the reservoir and the fluid, and the specific formula is as follows:
wherein, PresevoirAs a reservoir parameter, PfluidAs a parameter of the fluid, PdensityIs a density parameter; presevoir_1Reservoir parameter value, P, for the first sample point in the initial modelfluidThe fluid parameter value of the first sampling point in the initial model and the density parameter value of the first sampling point in the initial model. The initial model can be a low-pass filtering model constructed according to well data and geological frame data and used for representing an initial value of the elastic parameters and a real low-frequency trend of the elastic parameters in inversion solving.
According to the scheme provided by the embodiment of the specification, the longitudinal wave approximate model and the converted wave approximate model which directly represent the relation between the reservoir parameters and the fluid parameters and the longitudinal wave reflection coefficients and the converted wave reflection coefficients are utilized, the elastic parameters which represent the reservoir and the fluid are directly calculated on the basis of the well logging curve and the partial angle superposition data body, and the accumulated error caused by indirect calculation is reduced. Meanwhile, converted wave information and multiple items of constraint information are further added into the constructed objective function, so that the accuracy of an inversion result is greatly improved, and the obtained reservoir parameters and fluid parameters can be used for carrying out comprehensive analysis on the oil reservoir and guiding subsequent interpretation work.
Based on the solutions provided by the above embodiments in the present specification, the present specification further provides a specific scenario example to illustrate the practicability of the solutions provided by the embodiments in the present specification. Fig. 2 is a flowchart illustrating a method for determining a sexual parameter in an exemplary scenario provided in the present specification. As shown in fig. 2, the method may include the steps of:
s1: acquiring and processing logging data of a research area and a prestack seismic common reflection point gather;
s2: performing AVO attribute analysis according to the logging data and the common reflection point gather to determine a sub-angle scheme of the seismic data;
s3: respectively extracting wavelets of longitudinal waves and converted wave division angle superposition data based on the processed logging data and well-side seismic channel data;
s4: constructing longitudinal wave and converted wave approximate formulas capable of indicating reservoir and fluid characteristics according to the rock physical relationship;
s5: constructing an inversion target function by using the logging data, the common reflection point seismic gather and an approximate formula;
s6: solving the change rate of reservoir parameters and the change rate of fluid parameters according to the newly constructed objective function;
s7: and integrating the reflectivity parameters on the basis of the initial model to obtain elastic parameters for representing the reservoir and the fluid.
Based on the above scheme, the present specification further provides specific example comparative analysis, as shown in fig. 3 to 9, and specific comparative analysis results are as follows. Firstly, the selected sensitive fluid factors are different for different geological type regions, and FIC (F) is used for quantitative evaluation of the sensitivity of the fluid factorsA parameter Indicator coeffient) and establishing a fluid evaluation factor sensitivity Coefficient SfluidThe fluid discrimination capability of the fluid evaluation factor on the fluid can be characterized, and the specific expression is as follows:
in the above formula, S1And S2The fluid factor values for different types of fluids filling the formation pores are separated. SfluidHas a value of 0-200, if S1And S2When filled with the same fluid, then SfluidIs 0; s1And S2The larger the difference of (A), SfluidThe closer to 200. SfluidThe larger the value is, the higher the sensitivity of the identification factor to the fluid is, i.e. the stronger the ability to distinguish the fluid properties is, and the sensitivity of the fluid factor can be quantitatively evaluated by using the evaluation parameter.
The method is characterized in that adaptation is carried out on the basis of three typical sandstone models given by Hilterman to obtain basic parameters in the table 1, and the sensitivity coefficient of a common fluid evaluation factor (table 2) can be calculated by combining a fluid evaluation factor sensitivity coefficient formula. FIG. 3 is a graphical representation of the sensitivity of different fluid indicators in different reservoir conditions plotted according to Table 2. In fig. 3, a line 1 represents the sensitivity coefficient of the fluid discrimination factor obtained by the first sandstone model, a line 2 represents the sensitivity coefficient of the fluid discrimination factor obtained by the second sandstone model, and a line 3 represents the sensitivity coefficient of the fluid discrimination factor obtained by the third sandstone model. The sit-down symbols in fig. 3 are fluid evaluation factor numbers corresponding to table 2. As can be seen from Table 2 and FIG. 3, the target fluid parameter P calculated in the examples of the present specificationfluidThe fluid parameters according to which embodiments of the present description are based may effectively indicate pore fluid type, as opposed to other fluid factors, which may be more sensitive indications in different reservoirs.
TABLE 1 three sandstone model parameters
TABLE 2 fluid evaluation factor susceptibility
Fig. 4 shows a schematic diagram of theoretical data and initial model data of inversion tests. Wherein, the solid lines of 1, 3, 5, 7 and 9 represent theoretical values, and the solid lines of 2, 4, 6, 8 and 10 represent initial model values in the inversion process. 1. Line 2 represents compressional velocity, lines 3 and 4 represent shear velocity, lines 9 and 10 represent density, and lines 5 and 6 and lines 7 and 8 represent reservoir and fluid parameters calculated using compressional and shear velocity and density values, respectively.
Fig. 5 is a schematic diagram of an angle gather without noise obtained by convolution of the theoretical value and the rake wavelet in fig. 4 based on the Zeoppritz formula when the incident angles are 5 °, 15 °, 25 °, and 35 °, respectively. In fig. 5, (a) is a longitudinal wave seismic angle gather, and (b) is a converted wave seismic angle gather.
Fig. 6 is a schematic diagram of an angle gather after adding noise interference on the basis of the angle gather shown in fig. 5, in which (a) in fig. 6 is a longitudinal wave seismic angle gather, and (b) in fig. 6 is a converted wave angle gather, which is used to verify the noise immunity of the method proposed in the embodiment of the present specification.
Fig. 7 is a schematic diagram of results of reservoir and fluid parameters obtained by using a compressional wave approximation model and a converted wave approximation model (fig. 6 (a)) and indirect calculation (fig. 6 (b)) proposed in the embodiments of the present specification, respectively, based on data of the graph (b) in fig. 6, and based on individual compressional wave data. The solid lines 11 and 13 are reservoir parameter curves obtained by inversion, and the solid lines 12 and 14 are fluid parameter curves obtained by inversion. It can be seen from fig. 7 that although indirect calculation can obtain a solution that is more similar to the theoretical value, there is a larger error locally, and the result obtained by direct solution using the equation of the embodiment of the specification is more consistent with the theoretical value.
Fig. 8 is a schematic diagram of inversion of the reservoir parameter and fluid parameter extraction method under the common constraints of compressional and converted waves (fig. 8 (a)) and the compressional alone method (fig. 8 (b)) based on the data of the graph (a) in fig. 6 and the equations set forth in the embodiments of the present description, respectively. Where solid lines 15, 17 are inverted reservoir parameter results and solid lines 16, 18 are inverted fluid parameter results. As can be seen by comparing the graph (a) in fig. 8 with the graph (b) in fig. 8, the extracted reservoir and fluid parameters under the common constraints of compressional and converted waves are more accurate than the extracted parameters under the constraint of compressional waves alone.
To further verify the noise immunity of the embodiments of the present description, an inversion method comparison of the multi-wave (fig. 9 (a)) and compressional-alone (fig. 9 (b)) methods to directly extract reservoir parameters and fluid parameters was also performed on the data containing noise (fig. 6 (a)) plots. Where solid lines 19, 21 are inverted reservoir parameter results and solid lines 20, 22 are inverted fluid parameter results. Compared with a method for independently extracting longitudinal wave constraint, the method provided by the embodiment of the specification is more stable and has stronger noise resistance when the observation data contains noise interference.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. For details, reference may be made to the description of the related embodiments of the related processing, and details are not repeated herein.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
According to the method for determining the elastic parameters of the stratum, provided by one or more embodiments of the specification, the elastic parameters representing the reservoir and the fluid can be directly calculated on the basis of the angle-divided superposition data volume by using the inversion model directly representing the distribution characteristics of the reservoir parameters and the fluid parameters, indirect calculation is not needed, and the accumulated error introduced by the indirect calculation is reduced. And the converted wave information is added in the inversion process, so that the accuracy of the inversion result is greatly improved.
Based on the method for determining the formation elasticity parameter, one or more embodiments of the present disclosure further provide a device for determining the formation elasticity parameter. The apparatus may include systems, software (applications), modules, components, servers, etc. that utilize the methods described in the embodiments of the present specification in conjunction with hardware implementations as necessary. Based on the same innovative conception, embodiments of the present specification provide an apparatus as described in the following embodiments. Since the implementation scheme of the apparatus for solving the problem is similar to that of the method, the specific implementation of the apparatus in the embodiment of the present specification may refer to the implementation of the foregoing method, and repeated details 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. Specifically, fig. 10 is a schematic block diagram illustrating an embodiment of an apparatus for determining an elastic parameter of a formation, where as shown in fig. 10, the apparatus may include:
the data acquisition module 102 may be configured to acquire measured longitudinal wavelength division angle seismic data and converted wavelength division angle seismic data of a target work area;
an inversion function obtaining module 104, configured to obtain a target function representing a proximity relationship between actually measured seismic data and theoretical seismic data calculated based on elastic parameters, where the target function is constructed according to a longitudinal wave approximation model and a converted wave approximation model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters include reservoir parameters and fluid parameters;
the inversion module 106 may be configured to perform inversion processing on the longitudinal wavelength division angle seismic data and the converted wavelength division angle seismic data by using the target function, so as to obtain elastic parameter data of the target work area.
In another embodiment of the present specification, the compressional wave approximation model may include:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Is the density parameter of the lower medium; rfluidAs rate of change of fluid parameter, L1Is the fluid parameter of the underlying medium, L2Is the fluid parameter, k, of the underlying medium1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
In another embodiment of the present specification, the converted wave approximation model may include:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
In another embodiment of the present specification, the objective function may include:
wherein r represents longitudinal wave data determined according to a longitudinal wave approximation model; s represents converted wave data determined from a converted wave approximation model, W1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1A matrix consisting of wavelets for a longitudinal-wavelength-component angle superimposed data volume, C2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; Ω is a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is a low-frequency factor, and Gm is a low-frequency component of a reservoir parameter, a fluid parameter and a density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
It should be noted that the above-described apparatus may also include other embodiments according to the description of the method embodiment. The specific implementation manner may refer to the description of the related method embodiment, and is not described in detail herein.
The device for determining the elastic parameters of the stratum provided by one or more embodiments of the specification can directly calculate the elastic parameters representing the reservoir and the fluid on the basis of the angle-divided superposition data volume by using the inversion model directly representing the distribution characteristics of the reservoir parameters and the fluid parameters, does not need indirect calculation, and reduces the accumulated error introduced by the indirect calculation. And the converted wave information is added in the inversion process, so that the accuracy of the inversion result is greatly improved.
The method or apparatus provided by the present specification and described in the foregoing embodiments may implement service logic through a computer program and record the service logic on a storage medium, where the storage medium may be read and executed by a computer, so as to implement the effect of the solution described in the embodiments of the present specification. Accordingly, the present specification also provides an apparatus for determining a formation elasticity parameter, comprising a processor and a memory storing processor-executable instructions, which when executed by the processor, perform steps comprising the method of any one of the above embodiments.
The storage medium may include a physical device for storing information, and typically, the information is digitized and then stored using an electrical, magnetic, or optical media. The storage medium may include: devices that store information using electrical energy, such as various types of memory, e.g., RAM, ROM, etc.; devices that store information using magnetic energy, such as hard disks, floppy disks, tapes, core memories, bubble memories, and usb disks; devices that store information optically, such as CDs or DVDs. Of course, there are other ways of storing media that can be read, such as quantum memory, graphene memory, and so forth.
It should be noted that the above description of the apparatus according to the method embodiment may also include other embodiments. The specific implementation manner may refer to the description of the related method embodiment, and is not described in detail herein.
The apparatus for determining elastic parameters of a formation according to the above embodiment may directly calculate elastic parameters characterizing a reservoir and a fluid on the basis of a sub-angle superposition data volume by using an inversion model directly characterizing reservoir parameters and fluid parameter distribution characteristics, without indirect calculation, thereby reducing an accumulated error introduced by indirect calculation. And the converted wave information is added in the inversion process, so that the accuracy of the inversion result is greatly improved.
The present specification also provides a system for determining a formation elasticity parameter, which may be a stand-alone system for determining a formation elasticity parameter or may be implemented in a variety of computer data processing systems. The system may be a single server, or may include a server cluster, a system (including a distributed system), software (applications), an actual operating device, a logic gate device, a quantum computer, etc. using one or more of the methods or one or more of the example devices of the present specification, in combination with a terminal device implementing hardware as necessary. The system for determining a formation elasticity parameter may comprise at least one processor and a memory storing computer executable instructions which, when executed by the processor, implement the steps of the method of any one or more of the embodiments described above.
It should be noted that the above-mentioned system may also include other implementation manners according to the description of the method or apparatus embodiment, and specific implementation manners may refer to the description of the related method embodiment, which is not described in detail herein.
The system for determining the elastic parameters of the stratum in the embodiment can directly calculate the elastic parameters representing the reservoir and the fluid on the basis of the angle-divided superposition data volume by using the inversion model directly representing the reservoir parameters and the fluid parameter distribution characteristics, does not need indirect calculation, and reduces the accumulated error introduced by the indirect calculation. And the converted wave information is added in the inversion process, so that the accuracy of the inversion result is greatly improved.
The embodiments of the present description are not limited to what must be consistent with a standard data model/template or described in the embodiments of the present description. Certain industry standards, or implementations modified slightly from those described using custom modes or examples, may also achieve the same, equivalent, or similar, or other, contemplated implementations of the above-described examples. The embodiments using these modified or transformed data acquisition, storage, judgment, processing, etc. may still fall within the scope of the alternative embodiments of the present description.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. A method of determining an elastic parameter of a formation, comprising:
acquiring actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of a target work area;
obtaining a target function for representing the approximate relation between actually-measured seismic data and theoretical seismic data calculated based on elastic parameters, wherein the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters comprise reservoir parameters and fluid parameters;
and performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area.
2. The method of claim 1, wherein the compressional wave approximation model comprises:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Is the density parameter of the lower medium; rfluidAs rate of change of fluid parameter, L1Is the fluid parameter of the underlying medium, L2Is the fluid parameter, k, of the underlying medium1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
3. The method of claim 2, wherein the converted wave approximation model comprises:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
4. The method of claim 3, wherein the objective function comprises:
wherein r represents longitudinal wave data determined according to a longitudinal wave approximation model; s represents converted wave data determined from a converted wave approximation model, W1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1A matrix consisting of wavelets for a longitudinal-wavelength-component angle superimposed data volume, C2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; Ω is a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is a low-frequency factor, and Gm is a low-frequency component of a reservoir parameter, a fluid parameter and a density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
5. The method of claim 1, wherein the obtaining elastic parameter data of the target work area by performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function comprises:
performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data according to the target function to obtain a reservoir parameter change rate and a fluid parameter change rate;
and integrating the change rate of the reservoir parameters and the change rate of the fluid parameters to obtain the reservoir parameters and the fluid parameters.
6. An apparatus for determining an elastic parameter of a formation, comprising:
the data acquisition module is used for acquiring actually measured longitudinal wave division angle seismic data and converted wave division angle seismic data of a target work area;
the inversion function acquisition module is used for acquiring a target function for representing the approximate relationship between the actually measured seismic data and theoretical seismic data calculated based on elastic parameters, the target function is constructed according to a longitudinal wave approximate model and a converted wave approximate model for directly representing reservoir parameters and fluid parameter distribution characteristics, and the elastic parameters comprise reservoir parameters and fluid parameters;
and the inversion module is used for performing inversion processing on the longitudinal wave division angle seismic data and the converted wave division angle seismic data by using the target function to obtain elastic parameter data of the target work area.
7. The apparatus of claim 6, wherein the compressional wave approximation model comprises:
Rresevoir＝2(μ2ρ2-μ1ρ1)/(μ2ρ2+μ1ρ1)
Rfluid＝2(L2-L1)/(L2+L2)
where R (α) represents the longitudinal wave data, α is the average of the reflection angle and transmission angle of the longitudinal wave data, RresevoirIs the rate of change of reservoir parameter, mu2Shear modulus, μ, of the overlying medium1Is the shear modulus, ρ, of the underlying medium2Is the density parameter of the upper medium, p1Is a lower layer mediumA density parameter of the mass; rfluidAs rate of change of fluid parameter, L1Is the fluid parameter of the underlying medium, L2Is the fluid parameter, k, of the underlying medium1Is the square of the dry rock velocity ratio, k2The velocity ratio of saturated rocks is quadratic.
8. The apparatus of claim 7, wherein the converted wave approximation model comprises:
where s (α) represents the converted-wave data and β is the average of the reflection angle and transmission angle of the converted-wave data.
9. The apparatus of claim 8, wherein the objective function comprises:
wherein r represents longitudinal wave data determined according to a longitudinal wave approximation model; s represents converted wave data determined from a converted wave approximation model, W1For a matrix of wavelets of a longitudinal-wavelength-component angle superimposed data volume, W2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; c1A matrix consisting of wavelets for a longitudinal-wavelength-component angle superimposed data volume, C2A matrix composed of wavelets for converting the wavelength division angle superposition data volume; Ω is a correlation matrix; m istLow frequency components of the initial reservoir parameters, fluid parameters and density parameters; g is a low-frequency factor, and Gm is a low-frequency component of a reservoir parameter, a fluid parameter and a density parameter to be solved; lambda [ alpha ]1、λ2、λ3To adjust the weight parameters; and N is the number of sampling points of each seismic channel.
10. A system for determining a formation elasticity parameter, the system comprising at least one processor and a memory storing computer executable instructions which when executed by the processor implement the steps of the method of any one of claims 1 to 5.
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