CN112505761B - Reservoir gas content detection method and device - Google Patents
Reservoir gas content detection method and device Download PDFInfo
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Abstract
The invention provides a reservoir gas-containing property detection method and device. The reservoir gas-containing detection method comprises the following steps: acquiring logging data and seismic data; (2) Constructing a rock physical analysis quantity version based on the logging data; (3) Fitting a linear trend line of the water-containing sandstone based on the rock physical analysis quantity plate; (4) Constructing a gas-containing sandstone prediction factor based on the rock physical analysis quantity version and the water-containing sandstone linear trend line; (5) Substituting the seismic data into a calculation formula of the gas-containing sandstone prediction factor to obtain a gas-containing sandstone prediction factor seismic data volume; (6) And performing reservoir gas content detection based on the gas-containing sandstone prediction factor seismic data volume. The method can reduce the multi-solution of reservoir prediction and improve the precision of exploration and development.
Description
Technical Field
The invention relates to the field of geophysical exploration of petroleum, in particular to a method and a device for predicting a high-porosity hydrocarbon-containing sandstone reservoir.
Background
In the oil exploration process, prestack inversion and rock physics analysis technology are applied more and more, good application effects are obtained in different research blocks, the reservoir identification factor constructed on the basis of attributes such as longitudinal wave impedance, transverse wave impedance and density can realize the function of distinguishing sandstone reservoirs and mudstone cover layers to a certain extent, and the classical reservoir identification factor comprises: the longitudinal and transverse wave velocity ratio, the Poisson impedance, the Russell fluid factors and the like have different applicability to different identification factors in different work areas and basins, and sensitivity analysis is required in the practical application process. Under the general condition, identification factors with strong sensitivity to reservoir lithology and fluid need to be introduced into undetermined coefficients in the construction process, and the introduction of the undetermined coefficients enhances the applicability of attribute factors on one hand, and increases the artificial interference of reservoir prediction and the multi-solution of prediction results on the other hand, and further aggravates the uncontrollable property of the prediction results for the lack of rock physical basic data of a research block with low exploration degree.
An effective solution to the above problems is to determine reservoir identification factors in a data-driven manner, construct attribute factors with work area applicability based on collected data, fully utilize empirical data fitting and trend analysis, develop data mining in depth, and summarize local laws. However, the existing reservoir gas content detection method still has the defects of low precision and uncontrollable prediction result. Therefore, a method for detecting the gas content of the reservoir with higher precision is needed to be found.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a reservoir gas-containing property detection method, which can reduce the ambiguity of reservoir prediction and improve the accuracy of exploration and development.
Another object of the present invention is to provide a reservoir gas-containing property detection device.
In order to achieve the above object, in one aspect, the present invention provides a method for detecting reservoir gas-bearing property, wherein the method comprises: acquiring logging data and seismic data; (2) Constructing a rock physical analysis quantity version based on the logging data; (3) Fitting an aqueous sandstone linear trend line based on the petrophysical analysis quantity plate; (4) Constructing a gas-containing sandstone prediction factor based on the rock physical analysis quantity version and the water-containing sandstone linear trend line; (5) Substituting the seismic data into a calculation formula of the gas-containing sandstone prediction factor to obtain a gas-containing sandstone prediction factor seismic data volume; (6) And performing reservoir gas content detection based on the gas-containing sandstone prediction factor seismic data volume.
According to some embodiments of the invention, the logging data in step (1) comprises: longitudinal wave velocity curve, transverse wave velocity curve, density curve and well logging oil gas water interpretation result.
According to some specific embodiments of the invention, the seismic data in step (1) comprises: and obtaining longitudinal wave velocity, transverse wave velocity and density seismic data volume by pre-stack seismic inversion.
According to some embodiments of the present invention, in step (2), the method for constructing the petrophysical analysis quantitative plate based on the log data comprises: constructing a rock physics analysis quantity version based on a longitudinal wave velocity curve, a transverse wave velocity curve, a density curve and a logging oil-gas-water interpretation result in logging data, wherein the abscissa of the rock physics analysis quantity version is X, the ordinate of the rock physics analysis quantity version is Y, and X = rho/v s ，Y＝ρv p Rho is density in g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p Is the velocity of longitudinal waveIn Km/s.
According to some embodiments of the present invention, in the step (3), the method for fitting the linear trend line of the aqueous sandstone based on the petrophysical analysis quantitative plate comprises: in the rock physical analysis quantity version, selecting data points of a water-containing sandstone storage area of a target interval to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the trend line formula obtained by fitting is as follows:
Y＝kX+d
wherein X = ρ/v s ，Y＝ρv p ，
k is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the longitudinal wave velocity and is Km/s.
According to some specific embodiments of the present invention, in the step (4), the specific method for constructing the gas sand predicting factor based on the petrophysical analysis quantitative plate and the water-containing sandstone linear trend line comprises: constructing a calculation formula of the gas-containing sandstone prediction factor based on the compressional wave velocity, the shear wave velocity, the density curve and the linear trend line of the water-containing sandstone obtained by fitting, wherein the calculation formula is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
According to some specific embodiments of the present invention, the specific method for reservoir gas bearing detection based on the gas sand predictor seismic data volume comprises: and predicting and researching the distribution rule of the gas reservoir in the work area based on the gas-containing sandstone prediction factor seismic data volume, wherein the distribution rule corresponds to the distribution range of the gas-containing sandstone reservoir when the gas-containing sandstone prediction factor is smaller than a gas-containing sandstone prediction threshold value, corresponds to the distribution range of mudstone when the gas-containing sandstone prediction factor is larger than the mudstone prediction threshold value, and corresponds to the distribution range of the water-containing sandstone reservoir when the gas-containing sandstone prediction factor is positioned between the gas-containing sandstone prediction factor and the mudstone.
In another aspect, the present invention further provides a device for detecting reservoir gas content, wherein the device is used to implement the method for detecting reservoir gas content as claimed above, and the device includes: the input unit is used for inputting logging data and seismic data; the analysis unit is used for constructing a rock physical analysis quantity version based on the logging data; the fitting unit is used for fitting the linear trend line of the water-containing sandstone based on the rock physical analysis quantity version; the construction unit is used for constructing the gas-containing sandstone prediction factor based on the rock physical analysis quantity version and the water-containing sandstone linear trend line; the calculation unit is used for substituting the seismic data into a gas-containing sandstone prediction factor calculation formula to obtain a gas-containing sandstone prediction factor seismic data volume; and the detection unit is used for detecting the gas content of the reservoir based on the gas-containing sandstone prediction factor seismic data body.
According to some embodiments of the invention, the well log data comprises: longitudinal wave velocity curve, transverse wave velocity curve, density curve and well logging oil gas water interpretation result.
According to some embodiments of the invention, the seismic data comprises: and obtaining longitudinal wave velocity, transverse wave velocity and density seismic data volume by pre-stack seismic inversion.
According to some embodiments of the present invention, the method for constructing the petrophysical analysis quantitative plate based on the well log data comprises: constructing a rock physics analysis quantity version based on a longitudinal wave velocity curve, a transverse wave velocity curve, a density curve and a logging oil-gas-water interpretation result in logging data, wherein the abscissa of the rock physics analysis quantity version is X, the ordinate is Y, and X = rho/v s ，Y＝ρv p Rho is density in g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
According to some embodiments of the invention, the method for fitting the linear trend line of the aqueous sandstone based on the petrophysical analysis quantitative plate comprises: in the rock physical analysis quantity version, selecting data points of a water-containing sandstone storage area of a target interval to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the fitting is performed to obtain a water-containing sandstone linear trend lineThe trend line formula is: y = kX + d, wherein X = ρ/v s ，Y＝ρv p K is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity with the unit of Km/s, v p The unit is the longitudinal wave velocity and is Km/s.
According to some specific embodiments of the present invention, the specific method for constructing the gas sand prediction factor based on the petrophysical analysis quantitative plate and the water-containing sand linear trend line comprises the following steps: constructing a calculation formula of the gas-containing sandstone prediction factor based on the compressional wave velocity, the shear wave velocity, the density curve and the linear trend line of the water-containing sandstone obtained by fitting, wherein the calculation formula is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the longitudinal wave velocity and is Km/s.
According to some specific embodiments of the present invention, the specific method for reservoir gas bearing detection based on the gas sand predictor seismic data volume comprises: and predicting and researching the distribution rule of the gas reservoir in the work area based on the gas-containing sandstone prediction factor seismic data volume, wherein the distribution rule corresponds to the distribution range of the gas-containing sandstone reservoir when the gas-containing sandstone prediction factor is smaller than a gas-containing sandstone prediction threshold value, corresponds to the distribution range of mudstone when the gas-containing sandstone prediction factor is larger than the mudstone prediction threshold value, and corresponds to the distribution range of the water-containing sandstone reservoir when the gas-containing sandstone prediction factor is positioned between the gas-containing sandstone prediction factor and the mudstone.
The reservoir gas-containing detection method provided by the invention constructs a self-adaptive reservoir gas-containing detection attribute factor based on a rock physical analysis quantity version and elastic parameters of pre-stack inversion, in the implementation process, a linear trend line of a water-containing sandstone reservoir is fitted based on the rock physical quantity version, then a gas-containing sandstone prediction factor calculation formula is constructed by combining reservoir sensitivity analysis, and finally the gas-containing sandstone prediction factor seismic data is substituted into the pre-stack inversion elastic parameters to obtain a gas-containing sandstone prediction factor seismic data body of a research work area and perform reservoir gas-containing detection. The reservoir gas-containing detection method is based on a data-driven research idea, reduces interference of human factors, makes full use of effective information of the existing data as far as possible, reduces the multi-solution of reservoir prediction, and improves the precision of exploration and development.
Drawings
FIG. 1 is a flow chart of a method of detecting reservoir gas bearing in accordance with the present invention;
FIG. 2 is a block diagram of a reservoir gas bearing detection apparatus of the present invention;
FIG. 3 is a fitting analysis diagram of a rock physical quantity plate and a water-containing sandstone constructed in a target interval of a research work area in example 1 of the present invention;
FIG. 4 is a histogram of analysis of the sensitivity of the gas-bearing sandstone prediction factor in the target interval of the research work area in example 1 of the present invention;
FIG. 5 is a seismic profile of a gas sandstone prediction factor through a well at a target interval of a research work area in example 1 of the present invention;
fig. 6 is a planar distribution diagram of gas sand sandstone prediction factor in the target interval of the research work area in the embodiment 1 of the invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be apparent that the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Example 1
The embodiment provides a reservoir gas-bearing property detection method (the specific flow is shown in figure 1 in detail), which comprises the following steps:
step 101: inputting well log data and seismic data
In practice, the input logging data includes: the longitudinal wave velocity curve, the transverse wave velocity curve, the density curve and the well logging oil-gas-water interpretation result, the input seismic data comprise: and obtaining longitudinal wave velocity, transverse wave velocity and density seismic data volume by pre-stack seismic inversion.
Step 102: method for constructing rock physical analysis quantity version based on logging data
In the implementation process, a rock physical analysis quantity version is constructed based on an input logging curve and a logging oil-gas-water interpretation result, the abscissa of the quantity version is X, the ordinate of the quantity version is Y, and X = rho/v s ，Y＝ρv p Rho is density in g/cm 3 ,v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s. Fig. 3 shows a rock physical quantity plate of a target interval of a research work area constructed in the implementation, and as can be seen from the figure, there are obvious differences in distribution regions of different lithological and fluid-containing reservoirs in the quantity plate, wherein mudstone (dark dots) is mainly distributed in the upper right corner region of the quantity plate, gas-containing sandstone (light dots) is mainly distributed in the lower left corner region of the quantity plate, and water-containing sandstone (black dots, within oval circles) is distributed in a narrow region between the two. The distribution differences of different types of reservoirs provide theoretical basis for constructing the gas-containing sandstone prediction factor, and how to specifically describe the distribution range of the gas-containing sandstone reservoir is the key point of the next research.
Step 103: fitting water-containing sandstone linear trend line based on rock physical analysis quantity plate
In the implementation process, in the rock physical quantity version, selecting data points of a water-containing sandstone storage zone of a target interval to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the trend line formula obtained by fitting is as follows:
Y＝kX+d
wherein X = ρ/v s ，Y＝ρv p (ii) a k is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
In this embodiment, as shown in fig. 3, linear fitting is performed on the data points (within an elliptical circle) of the water-containing sandstone reservoir, the black solid line in the figure is a linear trend line obtained by fitting, and a trend line formula obtained by fitting is as follows:
Y＝-8.05*X+18.9
that is, k = -8.05,d = -18.9, and the fitting correlation coefficient is 0.84, indicating that the linear fitting relationship is good.
Step 104: and constructing a gas-containing sandstone prediction factor based on the rock physical analysis quantity version and the water-containing sandstone linear trend line.
In the implementation process, a calculation formula of the gas-containing sandstone prediction factor is constructed based on the input compressional wave velocity, shear wave velocity and density curve and the linear trend line of the water-containing sandstone obtained by fitting, and is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity with the unit of Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
In this embodiment, the slope k = -8.05 obtained in step 103 is substituted into a calculation formula of the gas-containing sandstone prediction factor to obtain a prediction factor applicable to the target interval of the research area, where the calculation formula is:
fig. 4 shows a gas-containing sandstone prediction factor sensitivity analysis histogram, wherein the abscissa represents a gas-containing sandstone prediction factor F, and the ordinate represents a percentage, and two black vertical solid lines in the histogram divide the entire region into three parts according to the numerical value of the gas-containing sandstone prediction factor, wherein the left light region (i.e., F < 0.245) corresponds to a gas-containing sandstone reservoir, the middle black region (i.e., F is greater than or equal to 0.245 and less than or equal to 0.315) corresponds to a water-containing sandstone reservoir, and the right dark region (i.e., F > 0.315) corresponds to mudstone.
Step 105: substituting the seismic data into the calculation formula of the gas-containing sandstone prediction factor to obtain a gas-containing sandstone prediction factor seismic data volume
In the implementation process, the input prestack inversion longitudinal wave velocity, transverse wave velocity and density seismic data volume is substituted into the gas-containing sandstone prediction factor calculation formula in the step 104, so that a gas-containing sandstone prediction factor seismic data volume in the range of the target zone of the research work area can be obtained, and a data base is provided for the subsequent gas-containing reservoir distribution range prediction.
Step 106: reservoir gas content detection based on gas sandstone prediction factor seismic data volume
In the implementation process, the distribution rule of the gas reservoir in the research work area is predicted by using the gas sandstone prediction factor seismic data volume based on the prediction factor sensitivity analysis result in the step 104, and the prediction result is shown in fig. 5 and 6. Fig. 5 shows a seismic profile of the gas-containing sandstone prediction factor passing through the well at the target interval of the research work area, wherein the dark area represents the gas-containing sandstone prediction factor with low value F <0.245, namely a gas-containing sandstone area, and the light area represents the gas-containing sandstone prediction factor with high value F >0.315, namely a mudstone area. According to the diagram, two sets of gas-containing sandstone reservoirs are obtained by predicting that a W-2 well and a W-3 well correspond to each other in the solid line ellipse range, a W-1 well corresponds to each other in the dotted line ellipse range, the prediction result is completely consistent with the oil testing result of three wells in a target interval, the oil testing result shows that the W-1 well is a water well, the W-2 well and the W-3 well are high-yield gas wells, and the geological research shows that the W-1 well is positioned below an oil-water interface, so that the target that the trap structure high point is higher than the oil-water interface is preferentially considered when the structure zone is subsequently deployed. Fig. 6 shows a gas sand prediction factor plane distribution diagram of a target interval of a research work area, wherein a dark color area represents a gas sand prediction factor low value F <0.245, namely a gas sand area, and a light color area represents a gas sand prediction factor high value F >0.315, namely a mudstone area. The distribution range and the distribution rule of the gas-containing sandstone in the research area can be seen from the figure, the prediction results of the three wells in the figure are consistent with the oil testing conclusion, and meanwhile, the W-2 well and the W-3 well belong to two different structural units, and a mudstone separation zone exists between the two structural units, so that the two structural units are treated differently when oil-water system analysis is carried out. The effectiveness of the method is verified through analysis of the embodiment, and effective technical support is provided for reservoir gas-bearing detection.
Example 2
The embodiment also provides a reservoir gas content detection device for implementing the reservoir gas content detection method, and as shown in fig. 2 in detail, the device includes:
an input unit 201 for inputting logging data and seismic data; the logging data comprise a longitudinal wave velocity curve, a transverse wave velocity curve, a density curve and a logging oil-gas-water interpretation result; the seismic data includes: and obtaining longitudinal wave velocity, transverse wave velocity and density by pre-stack seismic inversion.
The analysis unit 202 is used for constructing a rock physical analysis quantity version based on the logging data; the specific method comprises the following steps: constructing a rock physics analysis quantity version based on a longitudinal wave velocity curve, a transverse wave velocity curve, a density curve and a logging oil-gas-water interpretation result in logging data, wherein the abscissa of the rock physics analysis quantity version is X, the ordinate is Y, and X = rho/v s ，Y＝ρv p Rho is density in g/cm 3 ,v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
The fitting unit 203 is used for fitting the linear trend line of the water-containing sandstone based on the rock physical analysis quantity plate; the specific method comprises the following steps: in the rock physical analysis quantity version, selecting data points of a water-containing sandstone storage area of a target interval to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the trend line formula obtained by fitting is as follows:
Y＝kX+d
wherein X = ρ/v s ，Y＝ρv p (ii) a k is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the longitudinal wave velocity and is Km/s.
The construction unit 204 is used for constructing the gas-containing sandstone prediction factor based on the petrophysical analysis quantity version and the water-containing sandstone linear trend line; the specific method comprises the following steps:
constructing a calculation formula of the gas-containing sandstone prediction factor based on the longitudinal wave velocity, the transverse wave velocity, the density curve and the linear trend line of the water-containing sandstone obtained by fitting, wherein the calculation formula is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the velocity of the longitudinal wave, km/s.
And the calculating unit 205 is used for substituting the seismic data into the gas-containing sandstone prediction factor calculation formula to obtain a gas-containing sandstone prediction factor seismic data volume.
The detection unit 206 is used for detecting the reservoir gas content based on the gas-containing sandstone prediction factor seismic data volume; the specific method comprises the following steps: and predicting and researching the distribution rule of the gas reservoir in the work area based on the gas-containing sandstone prediction factor seismic data volume, wherein the distribution rule corresponds to the distribution range of the gas-containing sandstone reservoir when the gas-containing sandstone prediction factor is smaller than a gas-containing sandstone prediction threshold value, corresponds to the distribution range of mudstone when the gas-containing sandstone prediction factor is larger than the mudstone prediction threshold value, and corresponds to the distribution range of the water-containing sandstone reservoir when the gas-containing sandstone prediction factor is positioned between the gas-containing sandstone prediction factor and the mudstone prediction threshold value.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present invention, and are not intended to limit the scope of the present invention, and any modifications or equivalent substitutions made within the spirit and principle of the present invention should be covered by the claims of the present invention.
Claims (7)
1. A method of reservoir gas bearing detection, wherein the method comprises:
(1) Acquiring logging data and seismic data;
(2) Constructing a rock physical analysis quantity version based on the logging data;
(3) Fitting an aqueous sandstone linear trend line based on the petrophysical analysis quantity plate;
(4) Constructing a gas-containing sandstone prediction factor based on the rock physical analysis quantity version and the water-containing sandstone linear trend line;
(5) Substituting the seismic data into a calculation formula of the gas-containing sandstone prediction factor to obtain a gas-containing sandstone prediction factor seismic data volume;
(6) Performing reservoir gas bearing detection based on the gas bearing sandstone prediction factor seismic data volume;
in the step (3), the specific method for fitting the linear trend line of the aqueous sandstone based on the petrophysical analysis quantitative plate comprises the following steps:
in the rock physical analysis quantity version, selecting data points of a water-containing sandstone storage area of a target interval to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the trend line formula obtained by fitting is as follows:
Y＝kX+d
wherein X = ρ/v s ，Y＝ρv p ；
k is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity with the unit of Km/s, v p Is the longitudinal wave velocity, with the unit of Km/s;
in the step (4), the specific method for constructing the gas-containing sandstone prediction factor based on the petrophysical analysis quantitative plate and the water-containing sandstone linear trend line comprises the following steps:
constructing a calculation formula of the gas-containing sandstone prediction factor based on the compressional wave velocity, the shear wave velocity, the density curve and the linear trend line of the water-containing sandstone obtained by fitting, wherein the calculation formula is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p The unit is the longitudinal wave velocity and is Km/s.
2. The method of claim 1, wherein the logging data in step (1) comprises: longitudinal wave velocity curve, transverse wave velocity curve, density curve and well logging oil gas water interpretation result.
3. The method of claim 1 or 2, wherein the seismic data in step (1) comprises: and (3) obtaining the longitudinal wave velocity, the transverse wave velocity and the density by pre-stack seismic inversion.
4. The method of claim 1, wherein in step (6), the specific method for reservoir gas detection based on the gas sand predictor seismic data volume comprises:
and predicting and researching the distribution rule of the gas reservoir in the work area based on the gas-containing sandstone prediction factor seismic data volume, wherein the distribution rule corresponds to the distribution range of the gas-containing sandstone reservoir when the gas-containing sandstone prediction factor is smaller than a gas-containing sandstone prediction threshold value, corresponds to the distribution range of mudstone when the gas-containing sandstone prediction factor is larger than the mudstone prediction threshold value, and corresponds to the distribution range of the water-containing sandstone reservoir when the gas-containing sandstone prediction factor is positioned between the gas-containing sandstone prediction factor and the mudstone.
5. A reservoir gas content detection apparatus for implementing the reservoir gas content detection method according to any one of claims 1 to 4, the apparatus comprising:
the input unit is used for inputting logging data and seismic data;
the analysis unit is used for constructing a rock physical analysis quantity version based on the logging data;
the fitting unit is used for fitting the linear trend line of the water-containing sandstone based on the rock physical analysis quantity version; wherein the linear trend line of the water-containing sandstone is fitted based on the petrophysical analysis quantity plate and comprises the following steps: in a rock physics analysis quantity version, selecting data points of a water-containing sandstone storage layer area of a target layer section to perform linear fitting to obtain a water-containing sandstone linear trend line, wherein the trend line formula obtained by fitting is as follows:
Y＝kX+d
wherein X = ρ/v s ，Y＝ρv p ；
k is the slope, d is the intercept, ρ is the density in g/cm 3 ，v s Is the transverse wave velocity with the unit of Km/s, v p Is the longitudinal wave velocity, with the unit of Km/s;
the device comprises a construction unit, a calculation unit and a calculation unit, wherein the construction unit is used for constructing a gas-containing sandstone prediction factor based on a rock physical analysis quantity version and a water-containing sandstone linear trend line; and constructing a gas-containing sandstone prediction factor based on the petrophysical analysis quantity version and the water-containing sandstone linear trend line as follows: constructing a calculation formula of the gas-containing sandstone prediction factor based on the compressional wave velocity, the shear wave velocity, the density curve and the linear trend line of the water-containing sandstone obtained by fitting, wherein the calculation formula is as follows:
wherein F is a gas-containing sandstone prediction factor, k is a slope, rho is a density, and the unit is g/cm 3 ，v s Is the transverse wave velocity in Km/s, v p Is the longitudinal wave speed with the unit of Km/s;
the calculation unit is used for substituting the seismic data into a gas-containing sandstone prediction factor calculation formula to obtain a gas-containing sandstone prediction factor seismic data volume;
and the detection unit is used for detecting the gas content of the reservoir based on the gas-containing sandstone prediction factor seismic data body.
6. A reservoir gas fraction detection apparatus as claimed in claim 5, wherein the input unit is configured to input log data comprising: longitudinal wave velocity curve, transverse wave velocity curve, density curve and well logging oil gas water interpretation result.
7. A reservoir gas fraction detection apparatus as claimed in claim 5 or 6, wherein the input unit, the seismic data comprises: and obtaining longitudinal wave velocity, transverse wave velocity and density seismic data volume by pre-stack seismic inversion.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102854531A (en) * | 2012-09-11 | 2013-01-02 | 中国石油天然气股份有限公司 | Multi-scale rock physical plate method and device for reservoir hydrocarbon detection |
| CN103527184A (en) * | 2013-10-28 | 2014-01-22 | 北京大学 | Method and system for predicting dolomite reservoir |
| CN106597544A (en) * | 2016-11-25 | 2017-04-26 | 中国石油天然气股份有限公司 | Method and device for predicting brittleness of compact oil and gas reservoir |
| CN109115987A (en) * | 2018-07-20 | 2019-01-01 | 中国石油天然气股份有限公司 | Fluid factor evaluation method and device based on rock physical model |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012006604A2 (en) * | 2010-07-08 | 2012-01-12 | Geco Technology B.V. | Methods and Devices for Transformation of Collected Data for Improved Visualization Capability |
| US20150362623A1 (en) * | 2014-06-12 | 2015-12-17 | Westerngeco, Llc | Joint inversion of attributes |
| CN104698500A (en) * | 2015-04-07 | 2015-06-10 | 成都乔依赛斯石油科技有限公司 | Method for predicting reservoir lithogenous phase through geology and logging information |
| US10928536B2 (en) * | 2017-12-07 | 2021-02-23 | Saudi Arabian Oil Company | Mapping chemostratigraphic signatures of a reservoir with rock physics and seismic inversion |
-
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- 2020-10-28 CN CN202011175054.3A patent/CN112505761B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102854531A (en) * | 2012-09-11 | 2013-01-02 | 中国石油天然气股份有限公司 | Multi-scale rock physical plate method and device for reservoir hydrocarbon detection |
| CN103527184A (en) * | 2013-10-28 | 2014-01-22 | 北京大学 | Method and system for predicting dolomite reservoir |
| CN106597544A (en) * | 2016-11-25 | 2017-04-26 | 中国石油天然气股份有限公司 | Method and device for predicting brittleness of compact oil and gas reservoir |
| CN109115987A (en) * | 2018-07-20 | 2019-01-01 | 中国石油天然气股份有限公司 | Fluid factor evaluation method and device based on rock physical model |
Non-Patent Citations (5)
| Title |
|---|
| Reservoir fluid discrimination with an alternative fluid indicator based on rock physics templates;Lei Wang et al.;《2016 SEG International Exposition and 86th Annual Meeting》;20161231;第2292-2293页 * |
| Seismic screening for hydrocarbon prospects using rock-physics attributes;PER AVSETH et al.;《The Leading Edge》;20140331;第267-270页 * |
| 基于广义泊松阻尼因子的流体检测技术与应用;王磊等;《中国石油学会 2019 年物探技术研讨会》;20191231;第1085-1088页 * |
| 岩石物理模型分析在致密砂岩含气储层预测中的应用;王永刚等;《2015 年物探技术研讨会》;20151231;第528-532页 * |
| 岩石物理驱动下地震流体识别研究;印兴耀等;《中国科学: 地球科学》;20141222;第45卷(第1期);第8-21页 * |
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