CN117331123A - Fracture-cavity density inversion method and fracture-cavity reservoir prediction system - Google Patents
Fracture-cavity density inversion method and fracture-cavity reservoir prediction system Download PDFInfo
- Publication number
- CN117331123A CN117331123A CN202311464139.7A CN202311464139A CN117331123A CN 117331123 A CN117331123 A CN 117331123A CN 202311464139 A CN202311464139 A CN 202311464139A CN 117331123 A CN117331123 A CN 117331123A
- Authority
- CN
- China
- Prior art keywords
- fracture
- cavity
- azimuth
- representing
- medium
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000011161 development Methods 0.000 claims abstract description 40
- 238000004364 calculation method Methods 0.000 claims abstract description 24
- 239000011435 rock Substances 0.000 claims abstract description 19
- 238000012937 correction Methods 0.000 claims description 54
- 230000000694 effects Effects 0.000 claims description 8
- 230000009471 action Effects 0.000 claims description 6
- 230000007704 transition Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 230000001808 coupling effect Effects 0.000 claims description 3
- 230000006870 function Effects 0.000 claims description 3
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 abstract description 4
- 239000003345 natural gas Substances 0.000 abstract description 2
- 239000003209 petroleum derivative Substances 0.000 abstract description 2
- 241001598107 Imperata Species 0.000 description 9
- 230000009286 beneficial effect Effects 0.000 description 6
- 230000008859 change Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000005260 corrosion Methods 0.000 description 3
- 230000007797 corrosion Effects 0.000 description 3
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- 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. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/622—Velocity, density or impedance
- G01V2210/6224—Density
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/624—Reservoir parameters
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention discloses a fracture-cavity density inversion method and a fracture-cavity reservoir prediction system, which belong to the technical field of petroleum and natural gas exploration, and comprise the following steps: acquiring logging data, a logging curve and a wide-azimuth seismic trace set; modeling the fracture-cavity reservoir rock Dan Wuli, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in the HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir; pushing an azimuth seismic reflection coefficient equation of the fracture-cave reservoir; constructing an azimuth elastic impedance equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model; optimizing a wide-azimuth seismic gather, and carrying out pre-stack elastic impedance inversion based on a logging curve and a plurality of partial overlapped seismic data in different azimuth to obtain an azimuth elastic impedance body; inverting the density of the seam holes; the system performs fracture-cavity density inversion based on the method and predicts the fracture-cavity reservoir. The method solves the problem of insufficient earthquake prediction precision and stability of the fracture-seam tunnel reservoir.
Description
Technical Field
The invention belongs to the technical field of petroleum and natural gas exploration, and particularly relates to a fracture-cavity density inversion method and a fracture-cavity reservoir prediction system based on the inversion method.
Background
As the extent of hydrocarbon exploration becomes deeper, new types of reservoirs are becoming of interest, which are controlled by multiple factors such as fractures, erosion, etc. The new type of reservoir is characterized by small fractures, cracks and eroded pores with complex longitudinal structures, namely fracture-hole fracture type reservoirs (called fracture-hole reservoirs for short).
Early days, post-stack seismic attribute prediction methods were mainly developed for large-scale fracture-cavity reservoirs, such as: the method has the advantages of enhancing coherence, structure tensor, likelihood, gradient attribute and the like, and has a certain effect on large and medium scale fracture-cavity reservoir prediction. Aiming at a small-scale fracture-type reservoir, an ellipse fitting, transverse wave splitting, anisotropic inversion and other prediction methods are formed, wherein the ellipse fitting, transverse wave splitting and other methods are assumed to have a plurality of conditions, and the application conditions are harsh; the anisotropic inversion is mainly based on a linear sliding fracture model (Schoenberg) theory, and has certain adaptability to microcracks with smaller opening degrees. Recently, scholars research a fracture-cavity prediction technology based on an artificial intelligence algorithm, and utilize algorithms such as a Support Vector Machine (SVM), deep learning and the like to directly establish a nonlinear relation between an earthquake and an attribute thereof and a fracture-cavity reservoir, so that the fracture-cavity reservoir prediction precision can be effectively improved, but the stability and multiple solutions in the fracture-cavity reservoir prediction process are difficult to avoid due to lack of geophysical theory.
Disclosure of Invention
According to the fracture-cavity density inversion method and the fracture-cavity reservoir prediction system, fracture-cavity rock physical models are built, fracture-cavity development density parameter inversion based on the fracture-cavity reservoir rock physical models is performed according to Fourier series expansion theory, dimensions of an azimuth elastic resistance equation are effectively reduced, and the problem that fracture-control type karst fracture-cavity reservoir earthquake prediction accuracy and stability are insufficient is solved.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the invention provides a fracture-cavity density inversion method, which comprises the following steps:
s1, acquiring logging data, a logging curve and a wide-azimuth seismic trace set;
s2, modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in an HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
s3, deducing an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on an anisotropic parameter representing the fracture-cavity reservoir and an HTI medium seismic azimuth reflection coefficient approximation equation;
s4, constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
s5, optimizing and processing a wide-azimuth seismic gather, and carrying out pre-stack elastic impedance inversion based on a logging curve and a plurality of partial overlapped seismic data of different azimuth to obtain an azimuth elastic impedance body;
s6, inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model.
The beneficial effects of the invention are as follows: according to the fracture hole density inversion method provided by the invention, the fracture hole reservoir rock physical model is taken as a basis, fracture hole development density parameters are introduced, the anisotropy parameters of the fracture hole reservoir are effectively represented, the azimuth seismic reflection coefficient equation of the fracture hole reservoir is deduced, the azimuth elastic impedance equation of the fracture hole reservoir is constructed, the Fourier series expansion is carried out on the azimuth elastic impedance equation, the dimension of the azimuth elastic impedance equation is effectively reduced, the fracture hole fracture inversion precision is improved, and the stability and calculation efficiency of fracture hole reservoir prediction are enhanced; the method can characterize the characteristics of complex longitudinal structure, rapid transverse change and stronger heterogeneity of the fracture-cavity reservoir, and is more in line with the geological development rule of the fracture-cavity reservoir.
Further, the step S2 includes the following steps:
s21, obtaining an average wave field equivalent stiffness modulus of the fracture-cavity medium based on logging data and a Hudson rock physical model:
wherein,represents the mean wavefield equivalent stiffness modulus, +.>Represents the uniform medium elasticity coefficient of the seamless hole, +.>Represents the elastic coefficient of the anisotropic medium of the seam hole, +.>Representing a first order correction amount, +.>Representing a second order correction amount;
s22, obtaining an isotropic medium elasticity coefficient based on the average wave field equivalent stiffness modulus of the fracture-cavity fissures:
where λ represents the pull Mei Jishu of the first hole-free isotropic medium and μ represents the pull Mei Jishu of the second hole-free isotropic medium;
s23, calculating a correction term of the influence of fracture-cavity fracture action on the elastic parameter based on the isotropic medium elastic coefficient and the fracture-cavity development density parameter:
wherein,represents a first-order correction term, e represents a fracture-cavity development density parameter, < >>Representing a second order correction term, +.>Representing a third order correction term, +.>Representing a fourth first order correction term, +.>Representing a first order correction term,/->Representing a second order correction term +.>Representing a third order correction term,/->A fourth second order correction term, q represents a first reduced term, U 11 Representing a first elastic parameter associated with the fracture characteristics, U 33 Representing a second elastic parameter related to fracture characteristics, wherein the first-order correction quantity is a correction quantity of the influence of single fracture-cavity independent action on the elastic parameter, and the second-order correction quantity is a correction quantity of the influence of coupling action among different fracture-cavities on the elastic parameter;
s24, combining correction items of the influence of the fracture-cavity effect on the elasticity parameters and anisotropic parameters in the HTI medium, and calculating to obtain anisotropic parameters representing the fracture-cavity reservoir layer:
wherein ε (v) Representing the first anisotropic parameter, delta (v) Representing the second anisotropic parameter, gamma representing the third anisotropic parameter, g representing the square of the background medium transverse and longitudinal wave velocity ratio.
The beneficial effects of adopting the further scheme are as follows: the method is based on a Hudson rock physical model, effectively characterizes a vertical seepage zone lava structure, obtains an anisotropic parameter for characterizing a fracture-cavity reservoir by introducing fracture-cavity development density parameters, and provides a basis for deriving an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir.
Further, the step S3 includes the following steps:
s31, based on anisotropic parameters representing the fracture-cavity reservoir, the HTI medium azimuth seismic reflection coefficient approximation equation is sorted into the sum of an isotropic term and an anisotropic term according to the parameter merging similar term:
R(θ,φ)＝R iso +R ani
wherein R (theta, phi) represents the HTI medium azimuth seismic reflection coefficient, R iso Representing the reflection coefficient of isotropic medium, R ani Represents the reflection coefficient of the anisotropic medium, θ represents the incident angle, deltaV p Representing the longitudinal wave velocity difference between the lower medium and the upper medium, V p Representing the longitudinal wave velocity of the medium DeltaV s Representing the underlying mediumTransverse wave velocity difference with upper medium, V s Represents the transverse wave velocity of the medium, Δρ represents the density difference between the lower medium and the upper medium, ρ represents the density of the medium, φ represents the included angle between the direction of the measuring line and the dip hole trend, Δε (v) Representing the first anisotropic parameter difference between the lower medium and the upper medium, delta (v) The anisotropic parameter difference between the lower medium and the upper medium is represented, and delta gamma represents the third anisotropic parameter difference between the lower medium and the upper medium;
s32, obtaining an approximate term of the reflection coefficient under the isotropic medium according to the basic petrophysical relationship:
s33, substituting the fracture-cavity development density parameter into an anisotropic term to obtain an anisotropic reflection coefficient term for representing the fracture-cavity reservoir layer:
wherein deltae represents the difference of the fracture-cavity development density parameters between the lower medium and the upper medium;
s34, replacing an isotropic term with a reflection coefficient approximation term under an isotropic medium, replacing an anisotropic reflection coefficient term representing the fracture-cavity reservoir layer with an anisotropic term, and deducing an earthquake azimuth and earthquake reflection coefficient equation of the fracture-cavity reservoir layer:
wherein R' (theta, phi) represents the seismic azimuth reflection coefficient of the longitudinal structural fracture-cavity reservoir.
The beneficial effects of adopting the further scheme are as follows: according to the invention, according to the basic rock physical relationship and the fracture-cavity development density parameters, the isotropic items are replaced by the reflection coefficient approximate items under the isotropic medium, and the anisotropic items are replaced by the anisotropic reflection coefficient items representing the fracture-cavity reservoir, so that the dimension of the inversion of the unknown parameters is reduced, and the stability and the calculation efficiency are improved.
Further, the step S4 includes the following steps:
s41, obtaining an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir:
wherein AEI (θ, φ) represents azimuthal elastic impedance, EI 0 Mean value of elastic impedance lambda 0 Mean value of pull Mei Jishu, mu 0 Mean value of shear modulus, ρ 0 An average value of the density is represented, a (θ) represents a first index coefficient, b (θ) represents a second index coefficient, c (θ) represents a third index coefficient, and d (θ, Φ) represents a fourth index coefficient;
s42, orderTo simplify the azimuth elastic impedance equation, and calculate the second transition term:
EI A (θ,φ)＝AEI(θ,φ)A
wherein EI is A (θ, φ) represents a second transition term, A represents a first transition term;
s43, taking the logarithm of the second transition item to obtain the linearized azimuthal elastic impedance:
where ln represents a logarithmic function;
s44, performing Fourier series expansion on the linear azimuth elastic impedance to obtain a Fourier series expansion result of an azimuth elastic impedance equation:
lnEI A (θ,φ)＝B 0 +B 2 cos2φ+B 4 cos4φ
wherein B is 0 Zero-order Fourier coefficient representing azimuthal elastic impedance, B 2 Second order Fourier coefficient representing azimuthal elastic impedance, B 4 A fourth order Fourier coefficient representing azimuthal elastic impedance, where B 0 As background item, B 2 Correlating with incidence angle and fracture-cavity development density parameters for representing fracture-cavity development density, B 4 In relation to the incidence angle and the fracture-cavity development density parameters, sin is lower than 30 DEG at the incidence angle 2 θtan 2 θ≈0；
S45, ignoring a fourth-order Fourier coefficient of the azimuth elastic impedance, and obtaining a second-order Fourier coefficient calculation model according to a Fourier series expansion result of an azimuth elastic impedance equation:
wherein phi is i′ The included angle between the direction of the ith measuring line and the dip of the slot hole is shown, and N is the total included angle between the direction of the measuring line and the dip of the slot hole.
The beneficial effects of adopting the further scheme are as follows: according to the method, the linear azimuth elastic impedance is subjected to series expansion in a Fourier series expansion mode, so that a second-order Fourier coefficient calculation model of the azimuth elastic impedance is obtained, the nonlinear equation is effectively prevented from being solved in an iteration mode, the rapid inversion of the fracture-cavity reservoir is realized, the stability of a prediction method is enhanced, the calculation efficiency is improved, the fracture-cavity development density can be effectively represented, and the fracture-cavity fracture-type reservoir distribution range can be accurately predicted.
Further, the step S5 includes the following steps:
s51, sequentially carrying out denoising, leveling and cutting off treatment on the wide-azimuth seismic trace set to obtain a plurality of partially overlapped seismic data in different azimuth;
s52, based on the logging curve and the seismic data overlapped by a plurality of parts in different directions, obtaining the direction elastic impedance body through pre-stack elastic impedance inversion.
The beneficial effects of adopting the further scheme are as follows: according to the invention, pre-stack elastic impedance inversion is performed by using the optimized wide azimuth seismic trace set, so that an azimuth elastic impedance body is obtained, a foundation is provided for inversion to obtain the fracture-cavity density, and the predicted fracture-cavity reservoir layer is more in accordance with the geological development rule of the fracture-cavity reservoir layer.
On the other hand, the invention also provides a fracture-cavity reservoir prediction system based on a fracture-cavity density inversion method, which comprises the following steps:
the first module is used for acquiring logging data, logging curves and wide-azimuth seismic gathers;
the second module is used for modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in the HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
the third module is used for deriving an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on the anisotropic parameter representing the fracture-cavity reservoir and the HTI medium seismic azimuth reflection coefficient approximation equation;
the fourth module is used for constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
a fifth module, configured to optimally process the wide azimuth seismic gather, and perform pre-stack elastic impedance inversion based on the log and a plurality of partially overlapped seismic data with different azimuth, to obtain an azimuth elastic impedance body;
the sixth module is used for inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model;
and a seventh module, configured to predict and obtain a fracture-cavity reservoir distribution range based on the fracture-cavity density obtained by inversion.
The beneficial effects of the invention are as follows: the fracture-cavity reservoir prediction system based on the fracture-cavity density inversion method is a system correspondingly arranged by the method and is used for realizing the fracture-cavity density inversion method, and the realized fracture-cavity reservoir prediction result has the characteristics of complex longitudinal structure, rapid transverse change and stronger heterogeneity, is more in line with the geological development rule of the fracture-cavity reservoir, and has high prediction efficiency and strong stability.
Other advantages that are also present with respect to the present invention will be more detailed in the following examples.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart showing the steps of a method for inverting the density of a hole in embodiment 1 of the present invention.
FIG. 2 is a block diagram of a fracture-cavity reservoir prediction system based on a fracture-cavity density inversion method in embodiment 2 of the present invention.
FIG. 3 is a graph of anisotropy after physical modeling of single well log data and rock in example 2 of the present invention.
FIG. 4 is a forward plot of the variation of the top boundary reflection coefficient of the cogongrass group with azimuth angle and incidence angle in example 2 of the present invention.
FIG. 5 is a partially superimposed seismic profile of example 2 of the present invention with different azimuth and angle of incidence.
FIG. 6 is a schematic view of the azimuthal elastance of the pre-stack inversion of partial superimposed data in example 2 of the present invention.
FIG. 7 (a) is a schematic diagram of a fracture-hole fracture reservoir inversion profile achieved in accordance with the present invention in example 2 of the present invention.
FIG. 7 (b) is a schematic diagram of a fracture-hole fracture reservoir inversion profile achieved by the prior art method of example 2 of the present invention.
FIG. 8 is a plan view of a fracture and cave fracture reservoir prediction for a cogongrass group in example 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention.
Example 1:
as shown in fig. 1, in one embodiment of the present invention, the present invention provides a fracture-cavity density inversion method, which includes the following steps:
s1, acquiring logging data, a logging curve and a wide-azimuth seismic trace set;
s2, modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in an HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
the step S2 comprises the following steps:
s21, obtaining an average wave field equivalent stiffness modulus of the fracture-cavity medium based on logging data and a Hudson rock physical model:
wherein,represents the mean wavefield equivalent stiffness modulus, +.>Represents the uniform medium elasticity coefficient of the seamless hole, +.>Represents the elastic coefficient of the anisotropic medium of the seam hole, +.>Representing a first order correction amount, +.>Representing a second order correction amount; the fracture and corrosion effects of the carbonate rock stratum are controlled together, the fracture and corrosion effects are mainly controlled, the fracture and corrosion effects are small, the narrow coin characteristic is shown, and the vertical seepage zone karst structure can be well represented based on the Hudson rock physical model.
S22, obtaining an isotropic medium elasticity coefficient based on the average wave field equivalent stiffness modulus of the fracture-cavity fissures:
where λ represents the pull Mei Jishu of the first hole-free isotropic medium and μ represents the pull Mei Jishu of the second hole-free isotropic medium;
s23, calculating a correction term of the influence of fracture-cavity fracture action on the elastic parameter based on the isotropic medium elastic coefficient and the fracture-cavity development density parameter:
wherein,represents a first-order correction term, e represents a fracture-cavity development density parameter, < >>Representing a second order correction term, +.>Representing a third order correction term, +.>Representing a fourth first order correction term, +.>Representing a first order correction term,/->Representing a second order correction term +.>Representing a third order correction term,/->A fourth second order correction term, q represents a first reduced term, U 11 Representing a first elastic parameter associated with the fracture characteristics, U 33 Representing a second elastic parameter related to fracture characteristics, wherein the first-order correction quantity is a correction quantity of the influence of single fracture-cavity independent action on the elastic parameter, and the second-order correction quantity is a correction quantity of the influence of coupling action among different fracture-cavities on the elastic parameter;
s24, combining correction items of the influence of the fracture-cavity effect on the elasticity parameters and anisotropic parameters in the HTI medium, and calculating to obtain anisotropic parameters representing the fracture-cavity reservoir layer:
wherein ε (v) Representing the first anisotropic parameter, delta (v) Representing the second anisotropic parameter, gamma representing the third anisotropic parameter, g representing the square of the background medium transverse and longitudinal wave velocity ratio.
The anisotropy parameters in the HTI medium are derived from Huger (1996), and the calculation expression is as follows:
wherein C is 11 Represents a first correction term, C 13 Representing a second correction term, C 33 Represents a third correction term, C 44 Represent the fourth correction term, C 55 Represents a fifth correction term, C 66 Representing a sixth correction term;
s3, deducing an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on an anisotropic parameter representing the fracture-cavity reservoir and an HTI medium seismic azimuth reflection coefficient approximation equation;
the step S3 comprises the following steps:
s31, based on anisotropic parameters representing the fracture-cavity reservoir, the HTI medium azimuth seismic reflection coefficient approximation equation is sorted into the sum of an isotropic term and an anisotropic term according to the parameter merging similar term:
R(θ,φ)＝R iso +R ani
wherein R (theta, phi) represents the HTI medium azimuth seismic reflection coefficient,R iso representing the reflection coefficient of isotropic medium, R ani Represents the reflection coefficient of the anisotropic medium, θ represents the incident angle, deltaV p Representing the longitudinal wave velocity difference between the lower medium and the upper medium, V p Representing the longitudinal wave velocity of the medium DeltaV s Representing the transverse wave velocity difference between the lower medium and the upper medium, V s Represents the transverse wave velocity of the medium, Δρ represents the density difference between the lower medium and the upper medium, ρ represents the density of the medium, φ represents the included angle between the direction of the measuring line and the dip hole trend, Δε (v) Representing the first anisotropic parameter difference between the lower medium and the upper medium, delta (v) The anisotropic parameter difference between the lower medium and the upper medium is represented, and delta gamma represents the third anisotropic parameter difference between the lower medium and the upper medium;
the HTI medium seismic azimuth reflection coefficient approximate equation is obtained by deriving an azimuth AVO reflection coefficient approximate equation of the HTI medium according to a first-order disturbance theory by Huger (1998), and the specific calculation expression is as follows:
wherein DeltaZ p Represents the difference in longitudinal wave impedance between the lower medium and the upper medium,represents the average value of the longitudinal wave impedance on both sides of the medium interface, for example>Mean value of longitudinal wave velocity at both sides of medium interface, delta is expressed as difference of upper and lower medium parameters (lower layer minus upper layer), and +.>Representing the average value of parameters at two sides of a medium interface;
s32, obtaining an approximate term of the reflection coefficient under the isotropic medium according to the basic petrophysical relationship:
s33, substituting the fracture-cavity development density parameter into an anisotropic term to obtain an anisotropic reflection coefficient term for representing the fracture-cavity reservoir layer:
wherein deltae represents the difference of the fracture-cavity development density parameters between the lower medium and the upper medium;
s34, replacing an isotropic term with a reflection coefficient approximation term under an isotropic medium, replacing an anisotropic reflection coefficient term representing the fracture-cavity reservoir layer with an anisotropic term, and deducing an earthquake azimuth and earthquake reflection coefficient equation of the fracture-cavity reservoir layer:
wherein R' (theta, phi) represents the seismic azimuth reflection coefficient of the longitudinal structural fracture-cavity reservoir.
Compared with the method for calculating the seismic azimuth reflection coefficient of the longitudinal fracture-cavity reservoir provided by the invention, which is obtained by deriving the azimuth AVO reflection coefficient approximate equation of the HTI medium according to the first-order disturbance theory by Ruger (1998), the dimension of the inversion of the unknown parameters is reduced from 6 dimensions to 4 dimensions, and the method has certain advantages of stability, accuracy and calculation efficiency in the aspect of the inversion stability of the fracture-cavity reservoir.
S4, constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
the step S4 comprises the following steps:
s41, obtaining an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir:
wherein AEI (θ, φ) represents azimuthal elastic impedance, EI 0 Mean value of elastic impedance lambda 0 Mean value of pull Mei Jishu, mu 0 Mean value of shear modulus, ρ 0 An average value of the density is represented, a (θ) represents a first index coefficient, b (θ) represents a second index coefficient, c (θ) represents a third index coefficient, and d (θ, Φ) represents a fourth index coefficient; in the embodiment, the azimuth elastic impedance equation is obtained according to the idea of deriving the standardized elastic impedance by Whitcombe (2002);
s42, orderTo simplify the azimuth elastic impedance equation, and calculate the second transition term:
EI A (θ,φ)＝AEI(θ,φ)A
wherein EI is A (θ, φ) represents a second transition term, A represents a first transition term;
s43, taking the logarithm of the second transition item to obtain the linearized azimuthal elastic impedance:
where ln represents a logarithmic function;
s44, performing Fourier series expansion on the linear azimuth elastic impedance to obtain a Fourier series expansion result of an azimuth elastic impedance equation:
lnEI A (θ,φ)＝B 0 +B 2 cos2φ+B 4 cos4φ
wherein B is 0 Zero-order Fourier coefficient representing azimuthal elastic impedance, B 2 Second order Fourier coefficient representing azimuthal elastic impedance, B 4 A fourth order Fourier coefficient representing azimuthal elastic impedance, where B 0 As background item, B 2 Correlating with incidence angle and fracture-cavity development density parameters for representing fracture-cavity development density, B 4 In relation to the incidence angle and the fracture-cavity development density parameters, sin is lower than 30 DEG at the incidence angle 2 θtan 2 θ≈0；
S45, ignoring a fourth-order Fourier coefficient of the azimuth elastic impedance, and obtaining a second-order Fourier coefficient calculation model according to a Fourier series expansion result of an azimuth elastic impedance equation:
wherein phi is i′ The included angle between the direction of the ith measuring line and the dip of the slot hole is shown, and N is the total included angle between the direction of the measuring line and the dip of the slot hole.
S5, optimizing and processing a wide-azimuth seismic gather, and carrying out pre-stack elastic impedance inversion based on a logging curve and a plurality of partial overlapped seismic data of different azimuth to obtain an azimuth elastic impedance body;
the step S5 comprises the following steps:
s51, sequentially carrying out denoising, leveling and cutting off treatment on the wide-azimuth seismic trace set to obtain a plurality of partially overlapped seismic data in different azimuth;
s52, based on the logging curve and the seismic data overlapped by a plurality of parts in different directions, obtaining the direction elastic impedance body through pre-stack elastic impedance inversion.
S6, inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model.
Example 2:
in another embodiment of the present invention, as shown in fig. 2, based on the method of embodiment 1, the present invention provides a fracture-cavity reservoir prediction system based on a fracture-cavity density inversion method, including:
the first module is used for acquiring logging data, logging curves and wide-azimuth seismic gathers;
the second module is used for modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in the HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
the third module is used for deriving an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on the anisotropic parameter representing the fracture-cavity reservoir and the HTI medium seismic azimuth reflection coefficient approximation equation;
the fourth module is used for constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
a fifth module, configured to optimally process the wide azimuth seismic gather, and perform pre-stack elastic impedance inversion based on the log and a plurality of partially overlapped seismic data with different azimuth, to obtain an azimuth elastic impedance body;
the sixth module is used for inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model;
and a seventh module, configured to predict and obtain a fracture-cavity reservoir distribution range based on the fracture-cavity density obtained by inversion.
In a practical example of the invention, the invention performs fracture-cavity development density parameter inversion and fracture-cavity reservoir distribution range prediction on a fracture-cavity reservoir of a sea-phase carbonate rock stratum in the Yangtze river region from the Sichuan basin;
as shown in FIG. 3, the A-well two-stack cogongrass mouth group fracture-cavity reservoir interval log in the investigation region is shown, wherein Vp is longitudinal wave velocity, vs is transverse wave velocity, density is Density, fractreeDensity is fracture-cavity development Density, dip-angle fracture azimuth, through the fracture-cavity reservoirThe petrophysical calculation obtains an anisotropic parameter for characterizing the fracture-cavity reservoir, wherein the anisotropic parameter for characterizing the fracture-cavity reservoir comprises a first anisotropic parameter epsilon (v) Second anisotropy parameter delta (v) And a third anisotropic parameter γ;
as shown in fig. 4, the seismic slopes are partially overlapped with different azimuth angles and incident angles, wherein the circular marked line is a forward curve of the variation of the top boundary reflection coefficient of the cogongrass group along with the azimuth angle when the incident angle is 5 degrees, the square marked line is a forward curve of the variation of the top boundary reflection coefficient of the cogongrass group along with the azimuth angle when the incident angle is 15 degrees, and the triangular marked line is a forward curve of the variation of the top boundary reflection coefficient of the cogongrass group along with the azimuth angle when the incident angle is 25 degrees. On the basis of petrophysical forward modeling, calculating the reflection coefficient value of the top boundary of the cogongrass mouth group along with the change of azimuth angle and incidence angle by utilizing the seismic azimuth reflection coefficient of the push pilot fracture hole, and analyzing that the fracture hole reservoir layer has azimuth anisotropy characteristics, wherein in the embodiment, the fracture hole anisotropy corresponding to the information of the far channel (namely, the incidence angle of 25 ℃) is optimal;
as shown in fig. 5, after the optimization processing of the wide-azimuth seismic data ovg gather, the number of the partial overlapped seismic data of the Middle channel Middle (the incident angle is 11-20 degrees) and the Far channel Far (the incident angle is 21-30 degrees) is 12, namely, a plurality of partial overlapped seismic data in different azimuths are used for carrying out the pre-stack elastic impedance inversion on the azimuth elastic impedance body of the pre-stack elastic impedance inversion. The number of orientations after the optimization of the wide-azimuth seismic data ovg gather is usually even, such as 4 orientations, 6 orientations, 8 orientations, etc.
As shown in fig. 6, 12 azimuth elastic impedance data volumes were calculated using pre-stack elastic impedance inversion.
And calculating a second-order coefficient term in a Fourier series expansion of an azimuth elastic impedance equation by using a far-road incident angle of 25 degrees corresponding to the strongest anisotropy to obtain inverted fracture-cavity density, and predicting a fracture-cavity reservoir distribution range of the cogongrass site group, as shown in fig. 7 (a). As shown in FIG. 7 (b), the conventional post-stack fracture-cavity reservoir seismic inversion result is shown, in contrast, the fracture-cavity reservoir predicted by the method has the characteristics of complex longitudinal structure, rapid transverse change, stronger heterogeneity and the like, and is more in line with the geological development rule of the fracture-cavity reservoir.
As shown in fig. 8, the plan distribution diagram of the seam-hole reservoir layer of the cogongrass site group predicted by the method mainly develops near the fracture of the base along the northeast direction, wherein the karst effect of the middle section of the fault is strongest, the seam-hole reservoir layer relatively develops, and the development rule of the seam-hole reservoir layer is met, so that the seam-hole reservoir layer predicted by the method is accurate, and a reliable reference is provided for the exploration field of the seam-hole reservoir layer of the target area.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention.
Claims (6)
1. The fracture-cavity density inversion method is characterized by comprising the following steps of:
s1, acquiring logging data, a logging curve and a wide-azimuth seismic trace set;
s2, modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in an HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
s3, deducing an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on an anisotropic parameter representing the fracture-cavity reservoir and an HTI medium seismic azimuth reflection coefficient approximation equation;
s4, constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
s5, optimizing and processing a wide-azimuth seismic gather, and carrying out pre-stack elastic impedance inversion based on a logging curve and a plurality of partial overlapped seismic data of different azimuth to obtain an azimuth elastic impedance body;
s6, inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model.
2. The fracture-cave density inversion method according to claim 1, wherein said S2 comprises the steps of:
s21, obtaining an average wave field equivalent stiffness modulus of the fracture-cavity medium based on logging data and a Hudson rock physical model:
wherein,represents the mean wavefield equivalent stiffness modulus, +.>Represents the uniform medium elasticity coefficient of the seamless hole, +.>Represents the elastic coefficient of the anisotropic medium of the seam hole, +.>Representing a first order correction amount, +.>Representing a second order correction amount;
s22, obtaining an isotropic medium elasticity coefficient based on the average wave field equivalent stiffness modulus of the fracture-cavity fissures:
where λ represents the pull Mei Jishu of the first hole-free isotropic medium and μ represents the pull Mei Jishu of the second hole-free isotropic medium;
s23, calculating a correction term of the influence of fracture-cavity fracture action on the elastic parameter based on the isotropic medium elastic coefficient and the fracture-cavity development density parameter:
wherein,represents a first-order correction term, e represents a fracture-cavity development density parameter, < >>Representing a second order correction term, +.>Representing a third order correction term, +.>Representing a fourth first order correction term, +.>Representing a first order correction term,/->Representing a second order correction term +.>Representing a third order correction term,/->A fourth second order correction term, q represents a first reduced term, U 11 Representing a first elastic parameter associated with the fracture characteristics, U 33 Representing a second elastic parameter related to fracture characteristics, wherein the first-order correction quantity is a correction quantity of the influence of single fracture-cavity independent action on the elastic parameter, and the second-order correction quantity is a correction quantity of the influence of coupling action among different fracture-cavities on the elastic parameter;
s24, combining correction items of the influence of the fracture-cavity effect on the elasticity parameters and anisotropic parameters in the HTI medium, and calculating to obtain anisotropic parameters representing the fracture-cavity reservoir layer:
wherein ε (v) Representing the first anisotropic parameter, delta (v) Representing the second anisotropic parameter, gamma representing the third anisotropic parameter, g representing the square of the background medium transverse and longitudinal wave velocity ratio.
3. A method of fracture-cavity density inversion according to claim 2, wherein S3 comprises the steps of:
s31, based on anisotropic parameters representing the fracture-cavity reservoir, the HTI medium azimuth seismic reflection coefficient approximation equation is sorted into the sum of an isotropic term and an anisotropic term according to the parameter merging similar term:
R(θ,φ)＝R iso +R ani
wherein R (theta, phi) represents the HTI medium azimuth seismic reflection coefficient, R iso Representing the reflection coefficient of isotropic medium, R ani Represents the reflection coefficient of the anisotropic medium, θ represents the incident angle, deltaV p Representation ofLongitudinal wave velocity difference between lower medium and upper medium, V p Representing the longitudinal wave velocity of the medium DeltaV s Representing the transverse wave velocity difference between the lower medium and the upper medium, V s Represents the transverse wave velocity of the medium, Δρ represents the density difference between the lower medium and the upper medium, ρ represents the density of the medium, φ represents the included angle between the direction of the measuring line and the dip hole trend, Δε (v) Representing the first anisotropic parameter difference between the lower medium and the upper medium, delta (v) The anisotropic parameter difference between the lower medium and the upper medium is represented, and delta gamma represents the third anisotropic parameter difference between the lower medium and the upper medium;
s32, obtaining an approximate term of the reflection coefficient under the isotropic medium according to the basic petrophysical relationship:
s33, substituting the fracture-cavity development density parameter into an anisotropic term to obtain an anisotropic reflection coefficient term for representing the fracture-cavity reservoir layer:
wherein deltae represents the difference of the fracture-cavity development density parameters between the lower medium and the upper medium;
s34, replacing an isotropic term with a reflection coefficient approximation term under an isotropic medium, replacing an anisotropic reflection coefficient term representing the fracture-cavity reservoir layer with an anisotropic term, and deducing an earthquake azimuth and earthquake reflection coefficient equation of the fracture-cavity reservoir layer:
wherein R' (theta, phi) represents the seismic azimuth reflection coefficient of the longitudinal structural fracture-cavity reservoir.
4. A method of fracture-cavity density inversion according to claim 3, wherein S4 comprises the steps of:
s41, obtaining an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir:
wherein AEI (θ, φ) represents azimuthal elastic impedance, EI 0 Mean value of elastic impedance lambda 0 Mean value of pull Mei Jishu, mu 0 Mean value of shear modulus, ρ 0 An average value of the density is represented, a (θ) represents a first index coefficient, b (θ) represents a second index coefficient, c (θ) represents a third index coefficient, and d (θ, Φ) represents a fourth index coefficient;
s42, orderTo simplify the azimuth elastic impedance equation, and calculate the second transition term:
EI A (θ,φ)＝AEI(θ,φ)/A
wherein EI is A (θ, φ) represents a second transition term, A represents a first transition term;
s43, taking the logarithm of the second transition item to obtain the linearized azimuthal elastic impedance:
where ln represents a logarithmic function;
s44, performing Fourier series expansion on the linear azimuth elastic impedance to obtain a Fourier series expansion result of an azimuth elastic impedance equation:
lnEI A (θ,φ)＝B 0 +B 2 cos2φ+B 4 cos4φ
wherein B is 0 Zero-order Fourier coefficient representing azimuthal elastic impedance, B 2 Second order Fourier coefficient representing azimuthal elastic impedance, B 4 A fourth order Fourier coefficient representing azimuthal elastic impedance, where B 0 As background item, B 2 Correlating with incidence angle and fracture-cavity development density parameters for representing fracture-cavity development density, B 4 In relation to the incidence angle and the fracture-cavity development density parameters, sin is lower than 30 DEG at the incidence angle 2 θtan 2 θ≈0；
S45, ignoring a fourth-order Fourier coefficient of the azimuth elastic impedance, and obtaining a second-order Fourier coefficient calculation model according to a Fourier series expansion result of an azimuth elastic impedance equation:
wherein phi is i′ The included angle between the direction of the ith measuring line and the dip of the slot hole is shown, and N is the total included angle between the direction of the measuring line and the dip of the slot hole.
5. The fracture-cavity density inversion method of claim 4, wherein S5 comprises the steps of:
s51, sequentially carrying out denoising, leveling and cutting off treatment on the wide-azimuth seismic trace set to obtain a plurality of partially overlapped seismic data in different azimuth;
s52, based on the logging curve and the seismic data overlapped by a plurality of parts in different directions, obtaining the direction elastic impedance body through pre-stack elastic impedance inversion.
6. A fracture-cavity reservoir prediction system based on the fracture-cavity density inversion method of any one of claims 1-5, comprising:
the first module is used for acquiring logging data, logging curves and wide-azimuth seismic gathers;
the second module is used for modeling the fracture-cavity reservoir rock Dan Wuli based on logging data, introducing fracture-cavity development density parameters, and combining with anisotropic parameters in the HTI medium to obtain anisotropic parameters representing the fracture-cavity reservoir;
the third module is used for deriving an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir based on the anisotropic parameter representing the fracture-cavity reservoir and the HTI medium seismic azimuth reflection coefficient approximation equation;
the fourth module is used for constructing an azimuth elastic impedance equation of the fracture-cavity reservoir based on an azimuth seismic reflection coefficient equation of the fracture-cavity reservoir, and performing Fourier series expansion to obtain a second-order Fourier coefficient calculation model;
a fifth module, configured to optimally process the wide azimuth seismic gather, and perform pre-stack elastic impedance inversion based on the log and a plurality of partially overlapped seismic data with different azimuth, to obtain an azimuth elastic impedance body;
the sixth module is used for inverting to obtain the fracture-cavity density based on the azimuth elastic resistance body and the second-order Fourier coefficient calculation model;
and a seventh module, configured to predict and obtain a fracture-cavity reservoir distribution range based on the fracture-cavity density obtained by inversion.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311464139.7A CN117331123B (en) | 2023-11-06 | 2023-11-06 | Fracture-cavity density inversion method and fracture-cavity reservoir prediction system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311464139.7A CN117331123B (en) | 2023-11-06 | 2023-11-06 | Fracture-cavity density inversion method and fracture-cavity reservoir prediction system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117331123A true CN117331123A (en) | 2024-01-02 |
| CN117331123B CN117331123B (en) | 2024-04-02 |
Family
ID=89290427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311464139.7A Active CN117331123B (en) | 2023-11-06 | 2023-11-06 | Fracture-cavity density inversion method and fracture-cavity reservoir prediction system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117331123B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6058073A (en) * | 1999-03-30 | 2000-05-02 | Atlantic Richfield Company | Elastic impedance estimation for inversion of far offset seismic sections |
| US20160025880A1 (en) * | 2014-07-24 | 2016-01-28 | Conocophillips Company | Target-oriented process for estimating fracture attributes from seismic data |
| CN107831543A (en) * | 2017-09-29 | 2018-03-23 | 中国石油化工股份有限公司 | Prestack seismic inversion method and system |
| CN110873897A (en) * | 2018-09-04 | 2020-03-10 | 中国石油化工股份有限公司 | Crack prediction method and system based on orientation elastic impedance Fourier series expansion |
| CN113176612A (en) * | 2021-03-26 | 2021-07-27 | 中国石油大学(华东) | High-angle crack density inversion method |
| CN114609669A (en) * | 2022-05-10 | 2022-06-10 | 青岛油金能源科技有限公司 | HTI type fracture reservoir parameter prediction method and system based on azimuth elastic impedance |
| CN116148924A (en) * | 2023-03-10 | 2023-05-23 | 中国石油大学(华东) | Shale layer density prediction method based on statistical petrophysical and related equipment |
-
2023
- 2023-11-06 CN CN202311464139.7A patent/CN117331123B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6058073A (en) * | 1999-03-30 | 2000-05-02 | Atlantic Richfield Company | Elastic impedance estimation for inversion of far offset seismic sections |
| US20160025880A1 (en) * | 2014-07-24 | 2016-01-28 | Conocophillips Company | Target-oriented process for estimating fracture attributes from seismic data |
| CN107831543A (en) * | 2017-09-29 | 2018-03-23 | 中国石油化工股份有限公司 | Prestack seismic inversion method and system |
| CN110873897A (en) * | 2018-09-04 | 2020-03-10 | 中国石油化工股份有限公司 | Crack prediction method and system based on orientation elastic impedance Fourier series expansion |
| CN113176612A (en) * | 2021-03-26 | 2021-07-27 | 中国石油大学(华东) | High-angle crack density inversion method |
| CN114609669A (en) * | 2022-05-10 | 2022-06-10 | 青岛油金能源科技有限公司 | HTI type fracture reservoir parameter prediction method and system based on azimuth elastic impedance |
| CN116148924A (en) * | 2023-03-10 | 2023-05-23 | 中国石油大学(华东) | Shale layer density prediction method based on statistical petrophysical and related equipment |
Non-Patent Citations (1)
| Title |
|---|
| 潘新朋;张广智;印兴耀;: "岩石物理驱动的储层裂缝参数与物性参数概率地震反演方法", 地球物理学报, no. 02, 15 February 2018 (2018-02-15) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117331123B (en) | 2024-04-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8275589B2 (en) | Modeling a reservoir using a compartment model and a geomechanical model | |
| US7742875B2 (en) | Method for geologic modeling through hydrodynamics-based gridding (Hydro-Grids) | |
| US8359184B2 (en) | Method, program and computer system for scaling hydrocarbon reservoir model data | |
| CN111706317B (en) | Method for determining distribution condition of residual oil in hypotonic reservoir in encryption adjustment area | |
| CN112282744B (en) | Unconventional oil and gas reservoir well pattern deployment optimization method and device | |
| CN105093311A (en) | Stratum denudation thickness measurement method for superposition basin multi-phase difference upheaval region | |
| Chang et al. | Data assimilation of coupled fluid flow and geomechanics using the ensemble Kalman filter | |
| Yermekov et al. | Features of permeability anisotropy accounting in the hydrodynamic model | |
| CN112034521A (en) | Method for predicting overpressure of under-compacted and hydrocarbon-production mixed formation | |
| Wang et al. | The Development Characteristics and Distribution Predictions of the Paleogene Coal‐measure Source Rock in the Qiongdongnan Basin, Northern South China Sea | |
| CN107341850B (en) | Geological modeling method for single-point-dam reservoir structure of meandering river under development well pattern | |
| Alhusseini et al. | Estimation of initial oil in place for Buzurgan Oil Field by using volumetric method and reservoir simulation method | |
| CN111856573B (en) | Ancient stress inversion method | |
| CN117331123B (en) | Fracture-cavity density inversion method and fracture-cavity reservoir prediction system | |
| CN116047602B (en) | Type II hydrate saturation prediction method based on hydrocarbon production numerical simulation | |
| McLennan et al. | SAGD reservoir characterization using geostatistics: Application to the Athabasca oil sands, Alberta, Canada | |
| Zeng et al. | Local coupled Markov chain model for simulating varied stratigraphy | |
| CN112433248B (en) | Method for detecting hidden reservoir stratum in carbonate rock deposition environment | |
| CN112377104B (en) | Method and device for dynamically adjusting actual drilling track of tight sandstone gas reservoir horizontal well | |
| Liang | An ensemble Kalman filter module for automatic history matching | |
| Huerta et al. | Gas condensate field development plan by means of numerical compositional simulation | |
| Wardhana et al. | Exploring the overlooked seurula potential in Arun field; a preliminary study from outcrops and subsurface data in North Sumatra Basin | |
| Correia | Integration of reservoir characterization with history matching guided by pilot wells: Application to the Norne Field | |
| Li et al. | Uncertainty evaluation method and application of reservoir Lithofacies proportion under the condition of few wells | |
| US20230375744A1 (en) | Methods and systems for constraining subsurface models |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |