CN113534241B - Method for identifying reservoir by using azimuth frequency-dependent fluid factor - Google Patents

Method for identifying reservoir by using azimuth frequency-dependent fluid factor Download PDF

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CN113534241B
CN113534241B CN202110779032.6A CN202110779032A CN113534241B CN 113534241 B CN113534241 B CN 113534241B CN 202110779032 A CN202110779032 A CN 202110779032A CN 113534241 B CN113534241 B CN 113534241B
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罗鑫
文华国
陈学华
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Chengdu Univeristy of Technology
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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. for interpretation or for event detection
    • G01V1/282—Application of seismic models, synthetic seismograms
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
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    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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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
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    • G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
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Abstract

The invention belongs to the field of oil-gas seismic exploration, and provides an interpretation technology for realizing high-precision reservoir identification by using a dispersion fluid factor sensitive to a reservoir and combining azimuth seismic data. According to the method, firstly, an azimuth AVO formula directly related to frequency is obtained by constructing the fluid factors related to reservoir parameters, and then synchronous inversion of five types of dispersion factors is realized by using azimuth seismic data, so that the obtained new dispersion fluid factors have strong sensitivity to the reservoir, abnormal interference unrelated to the reservoir can be suppressed, the resolution is high, the transverse continuity is good, and the reservoir with thin thickness can be well identified.

Description

Method for identifying reservoir by using azimuth frequency-dependent fluid factor
Technical Field
The invention belongs to the field of processing and explaining of oil and gas seismic exploration data, and relates to an explaining technology for realizing inversion of new frequency dispersion fluid factors through a new frequency-related azimuth AVO formula and realizing high-precision reservoir identification by using new frequency dispersion parameters sensitive to a reservoir and wide-azimuth seismic data.
Background
The dispersion is the inherent characteristic of the fluid-containing reservoir, the attribute can be fully mined for reservoir identification, and the AVO inversion method depending on the frequency provides an effective technology for extracting dispersion abnormality related to the fluid-containing reservoir from actual seismic data. Nowadays, the AVO inversion technology relying on frequency forcibly introduces the frequency into a conventional AVO formula to perform frequency dispersion inversion, which is unreasonable, the AVO formula directly related to the frequency needs to be utilized to perform inversion, and a fluid factor sensitive to a reservoir is required to be constructed to improve the accuracy of reservoir prediction.
The sensitivity of different frequency dispersion parameters to the fluid is different, and the problem of the sensitivity of the frequency dispersion attribute to the fluid is considered, so that the frequency dispersion factor sensitive to the reservoir fluid can be obtained by the frequency dispersion parameter inversion based on the sensitivity analysis, and the reservoir prediction precision is further improved. With the development of the wide-azimuth seismic acquisition technology, the wide-azimuth pre-stack seismic data can be fully utilized to carry out inversion of frequency dispersion parameters so as to carry out high-precision prediction on a reservoir stratum. Therefore, the technology of the invention provides a method for reservoir identification by constructing a dispersion factor sensitive to a reservoir and combining wide-azimuth seismic data.
Disclosure of Invention
The invention provides a method for identifying a reservoir by using azimuth frequency-dependent fluid factors, which realizes synchronous inversion of five types of frequency dispersion factors by deriving an azimuth AVO formula directly related to frequency, and directly identifies the reservoir by using constructed sensitive frequency dispersion fluid factors related to parameters such as reservoir permeability, fluid viscosity and the like.
The invention aims to provide a method for identifying a reservoir by using an azimuth frequency-dependent fluid factor, which mainly comprises the following steps:
performing time-frequency transformation on pre-stack angle channel set data, and constructing a target function related to a new dispersion fluid factor;
r＝eD
in the formula (I), the compound is shown in the specification,
Figure BDA0003155467460000011
r is a column vector of reflection coefficients at m frequencies, which is m × n rows, e is a coefficient matrix arranged in m × n rows and 5 columns in the reflection coefficient formula at m frequencies, DM、Dμ、
Figure BDA0003155467460000012
And
Figure BDA0003155467460000013
respectively the dispersion degree of the longitudinal wave modulus, the transverse wave modulus, the normal weakness, the new fluid factor and the tangential weakness. M and μ represent the longitudinal and transverse moduli, δNAnd deltaTNormal and tangential weakness, psi, of the rock, respectivelynThe method is a parameter related to the square of fracture weakness and relaxation time (influenced by parameters such as fluid viscosity, rock permeability and fracture aspect ratio), namely a new constructed fluid identification factor, and the expression is as follows: psin＝δNΓ2，
In the formula:
Figure BDA0003155467460000021
in the formula etafIs the viscosity of the fluid, K is the permeability of the rock, KfIs the bulk modulus of the fluid, a is the fracture aspect ratio, and Γ is the relaxation time.
The reference frequency omega is selected0And solving the dispersion result corresponding to the five types of moduli under the reference frequency by using least squares: p, S, N, K, L, and substituting the result into vector r, and performing five types of dispersion factors by using the following formulaSynchronous inversion of the son:
D＝(eTe)-1eTr
the pre-stack seismic data of different directions of the research work area are utilized
Figure BDA0003155467460000022
The reservoir identification is further carried out by utilizing the result identification;
and fourthly, repeating the steps from the first step to the third step until all pre-stack seismic angle gathers of the whole work area are processed, and obtaining a three-dimensional reservoir prediction result of the whole work area.
The specific implementation principle of the invention is as follows:
based on an equivalent medium model of Hudson et al (1996), new stiffness matrix parameters related to fracture weakness and new fluid indicator factors are constructed by simplifying the stiffness matrix parameters, and an AVOA reflection coefficient formula related to frequency is derived by using the relation between a scattering function and a reflection coefficient. For HTI media, the stiffness matrix C can be expressed as:
Figure BDA0003155467460000023
wherein M is lambda +2 mu, e is fracture density, lambda and mu are Lame coefficients of the rock,
Figure BDA0003155467460000024
and U33Are important parameters related to fluid parameters (fluid viscosity, bulk modulus) and fracture properties (permeability, fracture aspect ratio). Here, we consider the fracture filled with fluid, then
Figure BDA0003155467460000025
And U33The expression of (a) is:
Figure BDA0003155467460000026
wherein ω is 2 π f, g is μ/M,
Figure BDA0003155467460000031
ηfis the viscosity of the fluid, K is the permeability of the rock, KfIs the bulk modulus of the fluid, a is the fracture aspect ratio, and Γ is the relaxation time.
Analysis shows that U33The real part of the imaginary loudness of (a) is small and can be ignored. Further obtain U33Approximate expression for the real part:
Figure BDA0003155467460000032
in addition, studies have shown that, in practical seismic applications,
Figure BDA0003155467460000033
is negligible and will fill fluid fractures
Figure BDA0003155467460000034
The abbreviation is:
Figure BDA0003155467460000035
the expression for the stiffness matrix element can be further derived:
C11＝M-MδN-ω2Mψn,
C12＝λ-λδN-ω2λψn,
C23＝λ-λ(1-2g)δN-ω2λ(1-2g)ψn,
C33＝M-λ(1-2g)δN-ω2λ(1-2g)ψn,
C44＝μ,C55＝μ-μδT,
C13＝C21＝C31＝C12,C32＝C23,C66＝C55,C22＝C33
in the formula, #n＝δNΓ2，ψnIs a parameter related to the fracture weakness and the square of the relaxation time (influenced by parameters such as fluid viscosity, rock permeability and fracture aspect ratio), and can be used as a new fluid identification factor, deltaN＝4e/[3g(1-g)]And deltaT＝16e/[3(3-2g)]Normal and tangential weakness of the rock, respectively.
The perturbations in the elements of the stiffness matrix can be further derived:
ΔC11＝(M+ΔM)-(M+ΔM)(δN+ΔδN)-ω2(M+ΔM)(ψn+Δψn)-(M-MδN-ω2Mψn)
≈ΔM-δNΔM-MΔδN-ω2Mψn-ω2ψnΔM
ΔC12≈Δλ-ΔλδN-λΔδN-ω2λΔψn-ω2ψnΔλ,
ΔC23≈Δλ-(1-2g)δNΔλ-λ(1-2g)ΔδN-ω2λ(1-2g)Δψn-ω2(1-2g)ψnΔλ,
ΔC33≈ΔM-(1-2g)δNΔλ-λ(1-2g)ΔδN-ω2λ(1-2g)Δψn-ω2(1-2g)ψnΔλ,
ΔC44＝Δμ,
ΔC55≈Δμ-δTΔμ-μΔδT,
ΔC13＝ΔC21＝ΔC31＝ΔC12,
ΔC32＝ΔC23,ΔC66＝ΔC55,ΔC22＝ΔC33
wherein Δ M and Δ μ are changes in longitudinal and shear moduli at both sides of the reflecting interface, respectively, and Δ δNAnd delta phinIs delta from both sides of the interfaceNAnd new fluid factor psinThe amount of change in (c). Assuming that the amount of disturbance on both sides of the interface is small, Δ M Δ δ can be ignoredN、ΔMΔψnAn item.
The general expression for the scattering function is:
Figure BDA0003155467460000041
in the formula, PiAnd PsPolarization vectors for the incident and scattered waves, respectively, can be expressed as:
Figure BDA0003155467460000042
in the formula, theta is the incident angle of the P wave,
Figure BDA0003155467460000043
for azimuth, under the weak scattering construction condition, the PP wave reflection coefficient and the scattering function have the following relationship:
Figure BDA0003155467460000044
then the above formula is available:
Figure BDA0003155467460000045
the above formula is a derived new longitudinal wave reflection coefficient formula, which is related to incidence angle, azimuth angle and frequency at the same time, and contains a fluid factor psi directly related to fluid characteristicsn. This formula can be used to analyze frequency dependent azimuthal AVO inversion.
Expanding the formula, neglecting density term and calculatingAt a reference frequency omega0The Taylor expansion is carried out, then:
Figure BDA0003155467460000046
in the formula (I), the compound is shown in the specification,
A′(θ)＝A(θ),B′(θ)＝B(θ),
Figure BDA0003155467460000051
Figure BDA0003155467460000052
Figure BDA0003155467460000053
order:
Figure BDA0003155467460000054
Figure BDA0003155467460000055
in the formula, DM、Dμ、
Figure BDA0003155467460000056
And
Figure BDA0003155467460000057
respectively the dispersion degree of the longitudinal wave modulus, the transverse wave modulus, the normal weakness, the new fluid factor and the tangential weakness.
When azimuth angle
Figure BDA0003155467460000058
When considering m frequencies omega1,ω2,…,ωmIn the case of (3), the column vector r defining the m × n rows is:
Figure BDA0003155467460000059
define e as a matrix of m × n rows and 5 columns:
Figure BDA00031554674600000510
then the objective function can be obtained:
r＝eD
in the formula (I), the compound is shown in the specification,
Figure BDA00031554674600000511
solving the objective function then requires in the orientation quantity r
Figure BDA0003155467460000061
ΔδN(t,ω0)，Δψn(t,ω0)，ΔδT(t,ω0) Let this be P, S, N, K, L, respectively.
Wherein, the solving process of P, S, N, K, L is as follows:
a) a (theta)i)，B(θi)，C(θi)，D(θi) And E (theta)i) Looking at the sampling time t as a function of the received channel n (one coefficient a, B, C, D, and E for each sample point), then:
A(θi)＝A(t,n),B(θi)＝B(t,n),C(θi)＝C(t,n),D(θi)＝D(t,n),E(θi)＝E(t,n)
and performing spectrum equalization processing on the AVO gather before stacking:
Figure BDA0003155467460000062
in the formula, w (f)iN) is a spectrum equalization operator,
Figure BDA0003155467460000063
is the time-frequency spectrum of the original prestack angle gather,
Figure BDA0003155467460000064
as a result of spectral equalization.
b) For a certain reference frequency omega0The following expression is given:
Figure BDA0003155467460000065
order to
Figure BDA0003155467460000066
Ai＝A(t,i)，Bi＝B(t,i)，Ci＝C(t,i)，Di＝D(t,i)，Ei＝E(t,i)，
Figure BDA0003155467460000067
N＝ΔδN(t,f0)，K＝Δψn(t,f0)，L＝ΔδT(t,f0) Then, the fitting error of the trace set is defined as:
Figure BDA0003155467460000068
to find the variables P, S, N, K and L that minimize the error of the above equation, the partial derivatives are calculated for the variables P, S, N, K and L using the above equation as follows:
Figure BDA0003155467460000071
let the above equation equal 0, then there is:
Figure BDA0003155467460000072
p, S, N, K, L can be obtained by solving the above formula.
Similarly, given different azimuth angles, P, S, N, K, L at different azimuth angles can be obtained, and the dispersion factors of different azimuth angles can be obtained.
The method for identifying the reservoir by the azimuth frequency-dependent fluid factor has the following advantages:
(1) the derived new azimuth AVO reflection coefficient formula is directly related to frequency and can be directly used for AVO inversion depending on frequency, so that the irrationality of forcibly introducing the frequency into the AVO formula in the conventional AVO inversion depending on the frequency is avoided;
(2) a new fluid factor directly related to the permeability of reservoir rock and the viscosity of fluid is constructed, and the factor has stronger sensitivity to a reservoir containing the fluid and can be used for high-precision reservoir prediction;
(3) the synchronous inversion of the five types of dispersion factors can be realized simultaneously, the obtained new dispersion factor has good identification capability on the reservoir, abnormal interference irrelevant to the reservoir can be suppressed, the reservoir abnormality is directly highlighted, the resolution is high, the transverse continuity is good, and the problem that the thin reservoir is difficult to identify can be solved;
(4) the wide-azimuth frequency dispersion factor inversion can be realized, the characteristics of the fractured reservoir can be better analyzed by using the wide-azimuth seismic data, and the parameters such as fracture weakness and the like have good effects on identifying the compact fractured reservoir.
Drawings
FIG. 1 is a graph of frequency and orientation dependent reflection coefficient contrast utilized by the present technology.
FIG. 2 is a comparison graph of single-pass results of five types of dispersion factors obtained by inversion of the present invention.
FIG. 3 is a new dispersion factor profile obtained by the work area inversion of the embodiment of the present invention.
Detailed Description
The specific embodiment of the invention is as follows:
inputting a pre-stack angle gather, performing time-frequency spectrum analysis on the angle gather, and generating amplitude spectrums under different frequencies;
secondly, amplitude spectrum equalization processing is carried out on the amplitude spectrums under different frequencies, and the interval velocity of the seismic data is obtained;
thirdly, selecting a reference frequency, and inverting the modulus change rate at the frequency by using least squares, namely solving P, S, N, K, L;
fourth giving azimuth angle
Figure BDA0003155467460000081
The obtained P, S, N, K, L is brought into an objective function, inversion solving is carried out, and a final dispersion attribute result under the azimuth angle is generated;
repeating the steps from the first step to the fourth step to obtain frequency dispersion factor results of all directions;
sixthly, identifying the reservoir by using the new frequency dispersion fluid factor result obtained in the step of the fifth;
and repeating the steps from the first step to the sixth step, processing all three-dimensional data of the research work area, predicting the reservoir stratum, extracting the slices along the layer, and analyzing to obtain the predicted planar spreading of the reservoir stratum of different target intervals of the whole work area.
In order to clearly express the technical advantages of the invention, the embodiments of the invention are further described in detail with reference to the drawings. The examples of the invention illustrate:
FIG. 1 is a graph of reflection coefficient versus angle of incidence and azimuth for different frequencies. The reflection coefficients under the conditions of frequencies of 10Hz, 20Hz, 30Hz, 40Hz and 50Hz are respectively compared, and the figure shows that the reflection coefficients are symmetrical at a position of 180 degrees along with the change of the azimuth angle, the reflection coefficients at the azimuth angle of 0-180 degrees are also symmetrical at a position of 90 degrees along with the azimuth angle, in addition, the difference of the reflection coefficients of different frequency components along with the change of the azimuth angle and the incidence angle is obviously larger, which indicates that the reflection coefficients have stronger sensitivity with the frequencies, and the characteristic can be used for carrying out the frequency-dependent azimuth AVO inversion.
FIG. 2 is a comparison graph of single-pass results of five types of dispersion factors obtained by inversion using the technique of the present invention. It can be seen from the figure that the four dispersion factors in the graphs a-d are all obviously interfered by irrelevant anomalies (shown by black arrows), so that favorable reservoirs are difficult to distinguish, and the newly constructed dispersion factor in the graph e maximally suppresses the anomalous interference of the rest layers, and only two reservoir positions have strong anomalous dispersion.
FIG. 3 is a new dispersion factor profile obtained by inversion of working area 1 of the example. According to the well logging curve, two sets of reservoirs are arranged at the position, and according to the predicted profile results, the two sets of reservoirs can be well identified by the new dispersion factor, so that the high resolution is achieved, the transverse continuity is good, and irrelevant background abnormal interference is suppressed.
The above examples are only for illustrating the present invention, and the implementation steps of the method and the like can be changed, and all equivalent changes and modifications based on the technical scheme of the present invention should not be excluded from the protection scope of the present invention.

Claims (4)

1. A method for identifying a reservoir by using an orientation frequency-dependent fluid factor is characterized by comprising the following specific steps:
performing time-frequency transformation on pre-stack angle channel set data, and constructing a target function related to a new dispersion fluid factor;
r＝eD
in the formula (I), the compound is shown in the specification,
Figure FDA0003560216230000011
r is a column vector of reflection coefficients at m frequencies, which is m × n rows, e is a coefficient matrix arranged in m × n rows and 5 columns in the reflection coefficient formula at m frequencies, DM、Dμ、
Figure FDA0003560216230000012
And
Figure FDA0003560216230000013
the dispersion degrees of the longitudinal wave modulus, the transverse wave modulus, the normal weakness, the new fluid factor and the tangential weakness are respectively shown, M and mu respectively represent the longitudinal wave modulus and the transverse wave modulus, and deltaNAnd deltaTNormal and tangential weakness, psi, of the rock, respectivelynIs a parameter related to the fracture weakness and the square of the relaxation time, wherein the relaxation time is influenced by parameters such as fluid viscosity, rock permeability, fracture aspect ratio and the likeAnd then, the parameter is a new fluid identification factor which is constructed, and the expression is as follows: psin＝δNΓ2，
In the formula:
Figure FDA0003560216230000014
in the formula etafIs the viscosity of the fluid, K is the permeability of the rock, KfIs the bulk modulus of the fluid, a is the fracture aspect ratio, and Γ is the relaxation time;
the reference frequency omega is selected0And solving the dispersion result corresponding to the five types of moduli under the reference frequency by using least squares: p, S, N, K, L, and substituting the result into the vector r, and performing synchronous inversion of five types of dispersion factors by using the following formula:
D＝(eTe)-1eTr
the pre-stack seismic data of different directions of the research work area are utilized
Figure FDA0003560216230000015
And then using the results to identify the reservoir;
and fourthly, repeating the steps from the first step to the third step until all pre-stack seismic angle gathers of the whole work area are processed, and obtaining a three-dimensional reservoir prediction result of the whole work area, wherein the prediction result can provide support for high-precision prediction of the reservoir.
2. A method of identifying a reservoir as claimed in claim 1 wherein: the formula adopted by inversion is directly related to frequency and can be directly used for frequency-dependent azimuth AVO inversion, the irrationality that frequency is forcibly introduced into the AVO formula in the conventional frequency-dependent AVO inversion is avoided, and the adopted azimuth AVO formula is as follows:
Figure FDA0003560216230000016
in the formula (I), the compound is shown in the specification,
A′(θ)＝A(θ),B′(θ)＝B(θ),
Figure FDA0003560216230000021
Figure FDA0003560216230000022
Figure FDA0003560216230000023
in the formula (I), the compound is shown in the specification,
Figure FDA0003560216230000024
B(θ)＝-4g sin2theta, theta is the incident angle,
Figure FDA0003560216230000025
where ω is the angular frequency, ω is 2 pi f, Δ M and Δ μ are the difference in longitudinal and transverse moduli of the upper and lower interfaces, g is μ/M, Δ δ isNAnd deltaTDifference between normal and tangential weakness of rock at upper and lower interfaces, Delta psinThe difference between the new flow factors above and below the interface.
3. A method of identifying a reservoir as claimed in claim 1 wherein: constructing a new fluid factor psi related to parameters such as fluid viscosity, rock permeability and fracture aspect rationThe factor may directly reflect the characteristics of the reservoir.
4. A method of identifying a reservoir as claimed in claim 1 wherein: the synchronous inversion of five types of frequency dispersion factors is realized, and the newly constructed frequency dispersion is obtainedFluid factor
Figure FDA0003560216230000026
The method has extremely high sensitivity to the reservoir, is hardly interfered by background elastic abnormity, has high resolution and good transverse continuity, and has extremely high precision for identifying the reservoir.
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US6614717B1 (en) * 2001-08-30 2003-09-02 Nonlinear Seismic Imaging, Inc. Time-lapse seismic using nonlinear seismic imaging
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