CN112748467A - Method and system for determining Russell fluid factor by utilizing seismic data - Google Patents
Method and system for determining Russell fluid factor by utilizing seismic data Download PDFInfo
- Publication number
- CN112748467A CN112748467A CN202011572815.9A CN202011572815A CN112748467A CN 112748467 A CN112748467 A CN 112748467A CN 202011572815 A CN202011572815 A CN 202011572815A CN 112748467 A CN112748467 A CN 112748467A
- Authority
- CN
- China
- Prior art keywords
- angle
- medium
- small
- rmd
- seismic
- 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
- 239000012530 fluid Substances 0.000 title claims abstract description 68
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000001914 filtration Methods 0.000 claims abstract description 7
- 239000011435 rock Substances 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000005553 drilling Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 229920006395 saturated elastomer Polymers 0.000 claims description 3
- 238000011282 treatment Methods 0.000 claims description 3
- 229930195733 hydrocarbon Natural products 0.000 abstract description 9
- 150000002430 hydrocarbons Chemical class 0.000 abstract description 9
- 239000004215 Carbon black (E152) Substances 0.000 abstract description 8
- 238000001514 detection method Methods 0.000 abstract description 6
- 238000004519 manufacturing process Methods 0.000 abstract description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 239000011148 porous material Substances 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
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
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 relates to a method and a system for determining Russell fluid factors by utilizing seismic data, wherein the method comprises the following steps: 1) firstly, performing explanatory processing on a prestack seismic angle gather, and then performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume; 2) extracting wavelets of the small, medium and large differential angle seismic data volumes, constructing small, medium and large angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by utilizing low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining the inversion results of the small, medium and large angle RMD _ EI; 3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body. The invention can meet the requirement of reservoir hydrocarbon detection in actual production and has high reliability.
Description
Technical Field
The invention relates to the technical field of geophysical exploration, in particular to a method and a system for determining Russell fluid factors by utilizing seismic data.
Background
The fluid indication parameters are the main identification basis for detecting underground reservoir hydrocarbons, and the pre-stack seismic inversion is the main technical means for calculating the fluid indication parameters. In order to improve the accuracy of hydrocarbon detection, researchers have been dedicated to improving the hydrocarbon identification sensitivity of fluid indicator parameters and increasing the reliability of the calculation method, but there are still many problems to be solved, which are limited by the complexity of the underground medium and the pathological solution of the seismic inversion method.
The Russell fluid factor is a fluid indication parameter which is proposed by Russell and others in 2003 based on a Biot-Gassmann pore elastic medium theory, and the elastic parameter can well reduce oil-water identification artifacts caused by reservoir pore heterogeneity, so that the underground medium oil-gas content can be reliably indicated, and the Russell fluid factor has sensitive reservoir hydrocarbon identification sensitivity. At present, pre-stack earthquakes are mostly taken as main bodies in the related industry, longitudinal wave velocity, transverse wave velocity and density parameters are calculated by adopting an AVO synchronous inversion method, and then three elastic parameters are further utilized to calculate Russell fluid factors. With the gradual turning of an oil and gas exploration target to deep, deep water and lithology targets, the conventional Russell fluid factor calculation method is difficult to meet the requirements of actual production, particularly for deep water and deep targets under the condition of few wells, the general quality of pre-stack seismic gather data of the targets is poor, the number of well data is limited by the condition of less number and the like, the accuracy of longitudinal wave velocity, transverse wave velocity and density parameters of pre-stack AVO synchronous inversion is low, the reliability of indirectly calculated Russell fluid factors is further influenced, and the requirements of reservoir hydrocarbon detection in actual production are difficult to meet.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method and a system for determining Russell fluid factors by using seismic data, which have high reliability and can meet the requirement of reservoir hydrocarbon detection in actual production.
In order to achieve the purpose, the invention adopts the following technical scheme:
the method for determining Russell fluid factor by using seismic data comprises the following steps:
1) acquiring data of a prestack seismic angle gather and a stratum velocity model, performing explanatory processing on the prestack seismic angle gather, and performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume;
2) calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI curves, extracting wavelets of small, medium and large differential angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining small, medium and large-angle RMD _ EI inversion results;
3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.
The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 1):
1.1) acquiring data of pre-stack seismic angle gather data and stratum velocity model data;
1.2) carrying out random noise removal and seismic homophase axis leveling treatment on the pre-stack seismic angle gather data;
1.3) carrying out sub-angle superposition processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes.
The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 1.3):
1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, and converting the offset and the incident angle by using the depth of a target layer and the maximum offset length according to the following conversion basis: the ratio of half of the offset distance to the depth is the tangent value of the incident angle;
1.3.2) comprehensively analyzing multiple factors of the theoretical maximum incident angle and the coverage times, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;
1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form small, medium and large-angle seismic data volumes.
The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 2):
2.1) calculating small-angle, medium-angle and large-angle RMD _ EI parameters by using a logging curve, and obtaining small-angle, medium-angle and large-angle RMD _ EI parameter curves;
2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large differential angle seismic data volumes, and calibrating the time depths of the small, medium and large differential angle seismic data volumes;
2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;
2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;
and 2.5) performing elastic impedance inversion of the RMD _ EI by using small-angle, medium-angle and large-branch-angle seismic data volumes and using a constraint sparse pulse inversion method to obtain the inversion results of the RMD _ EI at small angle, medium angle and large angle.
The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 2.1):
2.1.1) calculating Russell fluid factor F by formula (1) using compressional velocity, shear velocity and density log dataRCalculating the shear modulus mu through a formula (2);
in the formula, VpRepresenting the velocity of longitudinal waves; vsRepresents the shear wave velocity; ρ represents the rock density;
representing the square of the dry rock compressional-to-shear velocity ratio.
μ＝ρVs 2 (2)
In the formula, VsRepresents the shear wave velocity; ρ represents the rock density;
2.1.2) Russell-based fluid factor FRAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:
in the formula, FRRepresents Russell fluid factor; μ represents a shear modulus; ρ represents the rock density; θ represents an incident angle;
representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; fR0、μ0And ρ0Defined as the average of Russell fluid factor, shear modulus and density parameters, respectively; RMD _ EI0Is the normalization factor.
The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 3):
3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);
3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);
wherein t represents time; theta1Represents a small angle of incidence; theta2Represents the medium angle of incidence; theta3Represents a large angle of incidence;
3.3) solving the equation set constructed in the step 3.2), obtaining a result, and performing exponential operation on the result to obtain final Russell fluid factor data.
The invention discloses a system for determining Russell fluid factor by utilizing seismic data, which comprises the following components:
the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;
the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the layer position constraint, extracting small, medium and large-angle seismic wavelets, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;
and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.
Due to the adoption of the technical scheme, the invention has the following advantages:
according to the invention, on the basis of improving the AVO (amplitude versus offset) characterization of the pre-stack earthquake by using the pre-stack sub-angle stacking, the direct calculation of the Russell fluid factor is realized by using the pre-stack elastic impedance inversion, the conventional method that the longitudinal wave velocity, the transverse wave velocity and the density are obtained firstly and then the accumulated error introduced by the Russell fluid factor is calculated indirectly is avoided, and the calculation accuracy of the Russell fluid factor is improved. Therefore, the method can improve the hydrocarbon detection reliability of the complex geological target, particularly the deep water reservoir and the deep reservoir under the condition of few wells, and provides technical support for solving the hydrocarbon detection problem of the complex reservoir.
Drawings
FIG. 1 is a schematic flow diagram of a method of the present invention for calculating Russell fluid factor using seismic data;
FIG. 2 is a schematic flow chart of the present invention for obtaining a sub-angle seismic data volume;
FIG. 3 is a schematic diagram of a process for obtaining RMD _ EI data according to the present invention;
FIG. 4 is a schematic flow chart of the present invention for obtaining a Russell fluid factor based on RMD _ EI;
FIG. 5 is a schematic flow diagram of a Russell fluid factor calculation system in accordance with the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the objects, features and advantages of the invention can be more clearly understood. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the present invention, but are merely intended to illustrate the spirit of the technical solution of the present invention.
As shown in FIG. 1, the present invention provides a method for determining Russell fluid factor using seismic data, comprising the steps of:
1) data such as a prestack seismic angle gather and stratum velocity model data are obtained, the prestack seismic angle gather is subjected to explanatory processing, and then the stratum velocity model data are combined to carry out sub-angle stacking of the prestack seismic angle gather, so that a small, medium and large angle stacked sub-angle seismic data body is obtained.
As shown in fig. 2, the specific process of step 1) is as follows:
1.1) acquiring data of a prestack seismic angle trace set and stratum velocity model data;
1.2) carrying out treatments such as random noise removal, seismic in-phase axis leveling and the like on the pre-stack seismic angle gather;
1.3) carrying out sub-angle stacking processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes, wherein the specific process is as follows:
1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, converting the offset and the incident angle by using the depth of a target layer and the maximum offset length, and taking the conversion as the tangent value of the incident angle according to the ratio of half of the offset to the depth;
1.3.2) comprehensively analyzing multiple factors such as the theoretical maximum incident angle, the covering times and the like, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;
1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form a small-angle, medium-angle and large-angle seismic data body.
2) Calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI parameter curves, extracting wavelets of small, medium and large-angle sub-angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large-angle sub-angle seismic data volumes, and finally obtaining small, medium and large-angle inversion results of the RMD _ EI;
as shown in fig. 3, the specific process of step 2) is as follows:
2.1) calculating the RMD _ EI parameters of the small angle, the medium angle and the large angle by using the logging curve data, and obtaining the RMD _ EI parameter curves of the small angle, the medium angle and the large angle, wherein the specific process is as follows:
2.1.1) calculating Russell fluid factor F by using longitudinal wave velocity, transverse wave velocity and density logging curve data through formulas (1) and (2) respectivelyRAnd shear modulus μ:
in the formula, VpRepresenting the velocity of longitudinal waves; vsRepresents the shear wave velocity; ρ represents the rock density;
represents the square of the dry rock compressional-shear velocity ratio;
μ＝ρVs 2 (2)
in the formula, VsRepresents the shear wave velocity; ρ represents the rock density;
2.1.2) Russell-based fluid factor FRAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:
wherein θ represents an incident angle;
representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; fR0、μ0And ρ0Defined as Russell fluid factor, shear modulus and density, respectivelyAn average value of the parameter; RMD _ EI0Is the normalization factor.
2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large angle angular separation seismic data bodies, and carrying out time depth calibration on the small, medium and large angle angular separation seismic data bodies;
2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;
2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;
and 2.5) performing elastic impedance inversion of the RMD _ EI by using a constraint sparse pulse inversion method according to the sub-angle seismic data volumes of the small angle, the medium angle and the large angle to obtain the inversion results of the RMD _ EI of the small angle, the medium angle and the large angle.
And 3) carrying out logarithmic processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.
As shown in fig. 4, the specific process of step 3) is as follows:
3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);
3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);
wherein t represents time; theta1Represents a small angle of incidence; theta2Represents the medium angle of incidence; theta3Indicating a large angle of incidence.
3.3) solving the equation set constructed in the step 3.2), and carrying out exponential operation on the result to obtain final Russell fluid factor data.
The invention also provides a system for calculating Russell fluid factor by using seismic data, which comprises:
the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;
the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the horizon constraint, extracting seismic wavelets of small, medium and large-angle-divided seismic data volumes, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;
and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (7)
1. A method for determining Russell fluid factors using seismic data, comprising the steps of:
1) acquiring data of a prestack seismic angle gather and a stratum velocity model, performing explanatory processing on the prestack seismic angle gather, and performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume;
2) calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI curves, extracting wavelets of small, medium and large differential angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining small, medium and large-angle RMD _ EI inversion results;
3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.
2. Method according to claim 1, characterized in that said step 1) comprises the following sub-steps:
1.1) acquiring data of pre-stack seismic angle gather data and stratum velocity model data;
1.2) carrying out random noise removal and seismic homophase axis leveling treatment on the pre-stack seismic angle gather data;
1.3) carrying out sub-angle superposition processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes.
3. Method according to claim 2, characterized in that said step 1.3) comprises the following sub-steps:
1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, and converting the offset and the incident angle by using the depth of a target layer and the maximum offset length according to the following conversion basis: the ratio of half of the offset distance to the depth is the tangent value of the incident angle;
1.3.2) comprehensively analyzing multiple factors of the theoretical maximum incident angle and the coverage times, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;
1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form small, medium and large-angle seismic data volumes.
4. Method according to claim 1, characterized in that said step 2) comprises the following sub-steps:
2.1) calculating small-angle, medium-angle and large-angle RMD _ EI parameters by using a logging curve, and obtaining small-angle, medium-angle and large-angle RMD _ EI parameter curves;
2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large differential angle seismic data volumes, and calibrating the time depths of the small, medium and large differential angle seismic data volumes;
2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;
2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;
and 2.5) performing elastic impedance inversion of the RMD _ EI by using small-angle, medium-angle and large-branch-angle seismic data volumes and using a constraint sparse pulse inversion method to obtain the inversion results of the RMD _ EI at small angle, medium angle and large angle.
5. Method according to claim 4, characterized in that said step 2.1) comprises the following sub-steps:
2.1.1) calculating Russell fluid factor F by formula (1) using compressional velocity, shear velocity and density log dataRCalculating the shear modulus mu through a formula (2);
in the formula, VpRepresenting the velocity of longitudinal waves; vsRepresents the shear wave velocity; ρ represents the rock density;
represents the square of the dry rock compressional-shear velocity ratio;
μ＝ρVs 2 (2)
in the formula, VsRepresents the shear wave velocity; ρ represents the rock density;
2.1.2) Russell-based fluid factor FRAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:
in the formula, FRRepresents Russell fluid factor; μ represents a shear modulus; ρ represents the rock density; θ represents an incident angle;
representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; fR0、μ0And ρ0Defined as the average of Russell fluid factor, shear modulus and density parameters, respectively; RMD _ EI0Is the normalization factor.
6. Method according to claim 4, characterized in that said step 3) comprises the following sub-steps:
3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);
3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);
wherein t represents time; theta1Represents a small angle of incidence; theta2Represents the medium angle of incidence; theta3Represents a large angle of incidence;
3.3) solving the equation set constructed in the step 3.2), obtaining a result, and performing exponential operation on the result to obtain final Russell fluid factor data.
7. A system for determining Russell fluid factor using seismic data, comprising:
the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;
the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the layer position constraint, extracting small, medium and large-angle seismic wavelets, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;
and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011572815.9A CN112748467B (en) | 2020-12-24 | 2020-12-24 | Method and system for determining Russell fluid factor by utilizing seismic data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011572815.9A CN112748467B (en) | 2020-12-24 | 2020-12-24 | Method and system for determining Russell fluid factor by utilizing seismic data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112748467A true CN112748467A (en) | 2021-05-04 |
| CN112748467B CN112748467B (en) | 2022-10-14 |
Family
ID=75646244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011572815.9A Active CN112748467B (en) | 2020-12-24 | 2020-12-24 | Method and system for determining Russell fluid factor by utilizing seismic data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112748467B (en) |
Citations (6)
| 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 |
| US20050007876A1 (en) * | 2003-07-09 | 2005-01-13 | Gas Technology Institute | Determination of fluid properties of earth formations using stochastic inversion |
| CN101634716A (en) * | 2009-08-26 | 2010-01-27 | 中国石油大学(华东) | Fluid elastic impedance inversion technology |
| CN104714249A (en) * | 2014-11-07 | 2015-06-17 | 中国石油化工股份有限公司 | New method for directly extracting fluid factors |
| CN105510965A (en) * | 2015-12-29 | 2016-04-20 | 中国石油天然气股份有限公司 | Fluid identification method and fluid identification device |
| CN111077574A (en) * | 2019-12-30 | 2020-04-28 | 中国石油大学(北京) | Method, device and system for determining stratum elastic parameters |
-
2020
- 2020-12-24 CN CN202011572815.9A patent/CN112748467B/en active Active
Patent Citations (6)
| 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 |
| US20050007876A1 (en) * | 2003-07-09 | 2005-01-13 | Gas Technology Institute | Determination of fluid properties of earth formations using stochastic inversion |
| CN101634716A (en) * | 2009-08-26 | 2010-01-27 | 中国石油大学(华东) | Fluid elastic impedance inversion technology |
| CN104714249A (en) * | 2014-11-07 | 2015-06-17 | 中国石油化工股份有限公司 | New method for directly extracting fluid factors |
| CN105510965A (en) * | 2015-12-29 | 2016-04-20 | 中国石油天然气股份有限公司 | Fluid identification method and fluid identification device |
| CN111077574A (en) * | 2019-12-30 | 2020-04-28 | 中国石油大学(北京) | Method, device and system for determining stratum elastic parameters |
Non-Patent Citations (5)
| Title |
|---|
| BRIAN H. RUSSELL ET AL.: "Fluid-property discrimination with AVO: A Biot-Gassmann perspective", 《CREWES RESEARCH REPORT》 * |
| SHIXIN ZHANG ET AL.: "Fluid discrimination study from Fluid Elastic Impedance (FEI)", 《SEG HOUSTON 2009 INTERNATIONAL EXPOSITION AND ANNUAL MEETING》 * |
| 印兴耀等: "针对深层流体识别的两项弹性阻抗反演与Ｒｕｓｓｅｌｌ流体因子直接估算方法研究", 《地球物理学报》 * |
| 张世鑫: "基于地震信息的流体识别方法研究与应用", 《万方数据》 * |
| 张世鑫等: "适于Russell流体因子提取的孔隙弹性介质反射系数近似方程", 《石油物探》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112748467B (en) | 2022-10-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113759425B (en) | Method and system for evaluating filling characteristics of deep paleo-karst reservoir stratum by well-seismic combination | |
| WO2017024702A1 (en) | Inversion system for ray elastic parameter | |
| CN113759424B (en) | Karst reservoir filling analysis method and system based on spectral decomposition and machine learning | |
| Dolan et al. | The broad-band fractal nature of heterogeneity in the upper crust from petrophysical logs | |
| WO2016008105A1 (en) | Post-stack wave impedance inversion method based on cauchy distribution | |
| CN111897011B (en) | Reservoir pore characteristic determination method, device and equipment | |
| US20160334528A1 (en) | Systems and methods for characterizing subterranean formations utilizing azimuthal data | |
| CN114994758B (en) | Wave impedance extraction and structure characterization method and system for carbonate rock fracture control reservoir | |
| CN106842326B (en) | Sand-mud interbed CO2 geological sequestration time-lapse seismic forward modeling method during non-transverse-wave velocity logging | |
| CN112114380A (en) | Prediction method for conglomerate oil reservoir | |
| CN110646850B (en) | Interlayer earthquake prediction method and device | |
| CN113552624B (en) | Porosity prediction method and device | |
| CN112748467B (en) | Method and system for determining Russell fluid factor by utilizing seismic data | |
| CN113109875B (en) | Inversion method of carbonate rock reservoir under full waveform velocity field constraint | |
| CN111077574A (en) | Method, device and system for determining stratum elastic parameters | |
| Fu et al. | Rock property-and seismic-attribute analysis of a chert reservoir in the Devonian Thirty-one Formation, west Texas, USA | |
| CN112130211A (en) | Method and system for calculating Gassmann fluid items | |
| CN115857047A (en) | Comprehensive prediction method for seismic reservoir | |
| CN112906465A (en) | Coal measure stratum acoustic curve reconstruction method and system based on stratum factors | |
| CN113806674A (en) | Method and device for quantifying longitudinal dimension of ancient river channel, electronic equipment and storage medium | |
| CN101581791A (en) | Method for extracting pre-stack hydrocarbon detection section of seismic data with low signal-to-noise ratio | |
| CN110850504B (en) | Shale density parameter prestack inversion method based on uranium curve quasi-impedance constraint | |
| CN111045083A (en) | Reservoir gas-containing property detection method | |
| Bouchaala et al. | Azimuthal Investigation of a Fractured Carbonate Reservoir | |
| CN104516021A (en) | Ray elastic parameter inversion method capable of improving stability and precision of analysis formula |
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 |