CN112505764B - High-porosity hydrocarbon-containing sandstone reservoir prediction method and device - Google Patents
High-porosity hydrocarbon-containing sandstone reservoir prediction method and device Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/303—Analysis for determining velocity profiles or travel times
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6161—Seismic or acoustic, e.g. land or sea measurements
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6169—Data from specific type of measurement using well-logging
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- 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
- G01V2210/6222—Velocity; travel time
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- 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
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- 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
- G01V2210/6226—Impedance
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- 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
- G01V2210/6244—Porosity
Abstract
The invention provides a method and a device for predicting a high-porosity hydrocarbon-containing sandstone reservoir. The reservoir prediction method comprises the following steps: (1) Acquiring well logging curve data and longitudinal and transverse wave impedance seismic data of a work area; (2) Constructing a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor with two-dimensional undetermined parameters based on the logging curve data obtained in the step (1); (3) Constructing an objective function based on the hydrocarbon-containing pore attributes and the high-pore hydrocarbon-containing sandstone reservoir discrimination factors obtained in the step (2); (4) Solving the objective function to obtain undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors; (5) And calculating a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor seismic data body and carrying out reservoir prediction. The reservoir prediction method effectively ensures the accuracy of reservoir prediction and reduces the exploration risk.
Description
Technical Field
The invention relates to the field of petroleum geophysical exploration, in particular to a method and a device for predicting a high-porosity hydrocarbon-containing sandstone reservoir.
Background
With the progress of seismic exploration technology, reservoir prediction means are continuously updated and iterated, and petroleum exploration targets are developed in the direction of refinement and complexity. Conventional reservoir prediction techniques based on elastic, single-phase fluid saturation are increasingly challenged in terms of prediction accuracy and effectiveness, especially for lithologic hydrocarbon reservoir exploration and reservoir description of multiphase fluid saturated rock where the expected accuracy requirements are difficult to achieve. In recent years, with the development of petrophysical theory, reservoir prediction technology based on elastic information is receiving more and more attention, and theoretical research considers that non-zero offset seismic data contains more reservoir fluid information, especially transverse wave velocity and density properties. Based on petrophysical analysis, in the aspect of earthquake prediction, the pre-stack inversion is combined with the fluid factor construction, so that the accuracy of lithology prediction and fluid detection is effectively improved; in the logging interpretation method, the logging interpretation method based on elastic information such as longitudinal wave speed, density and the like greatly enriches the method theory of stratum lithology and reservoir physical property interpretation, and improves the accuracy of reservoir prediction. In theory, the logging interpretation method based on the elastic information has better physical consistency with the seismic exploration compared with the logging interpretation means based on the electrical information, can effectively ensure the comparability of detection results of different scales, is beneficial to the joint application of logging and seismic information, and promotes the full linkage and fusion application of the two scale information. Based on longitudinal and transverse wave speed and density information, geophysicists in recent years propose various methods for describing lithology and physical properties of reservoirs, so that the purpose of fine reservoir prediction is achieved to a certain extent and in certain block ranges, and theoretical basis and guidance methods are provided for logging interpretation methods based on elastic information, wherein the method comprises the following steps: reservoir mudstone baseline method proposed by Smith and Gidlow (1987), la Mei Jishu intersection analysis method proposed by Goodway (1997), elastic impedance theory proposed by Connolly (1999), poisson impedance attribute proposed by Quakenbus (2006), and the like. Although the former research method is widely applied in actual oilfield development and has better application effect, certain limitation exists, and the selection of the applicable exploration method according to local conditions is a necessary means for ensuring the exploration success rate for various complicated geological problems of different work areas. Therefore, there is a need to find reservoir prediction methods with high accuracy and low exploration risk.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a method for predicting a high-porosity hydrocarbon-containing sandstone reservoir, which effectively ensures the accuracy of reservoir prediction and reduces the exploration risk.
It is another object of the present invention to provide a highly porous hydrocarbon-bearing sandstone reservoir prediction device.
To achieve the above object, in one aspect, the present invention provides a method for predicting a highly porous hydrocarbon-containing sandstone reservoir, wherein the method comprises: (1) Acquiring well logging curve data and longitudinal and transverse wave impedance seismic data of a work area; (2) Constructing a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor with two-dimensional undetermined parameters based on the logging curve data obtained in the step (1); (3) Constructing an objective function based on the hydrocarbon-containing pore attributes and the high-pore hydrocarbon-containing sandstone reservoir discrimination factors obtained in the step (2); (4) Solving the objective function to obtain undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors; (5) And (3) calculating a high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor seismic data body according to the undetermined parameter value and the longitudinal wave impedance seismic data in the step (1) and carrying out reservoir prediction.
According to some embodiments of the invention, the log data includes longitudinal wave velocity, transverse wave velocity, density, porosity, and water saturation profile.
According to some embodiments of the invention, the compressional impedance, shear impedance seismic data can be obtained based on conventional pre-stack inversion.
According to some embodiments of the invention, the calculation formula of the high porosity hydrocarbon-containing sandstone reservoir discrimination factor is:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir, and is a function of undetermined parameters x, y, x and y are undetermined parameters, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave velocity is given in m/s.
According to some embodiments of the invention, the hydrocarbon-containing pore properties are calculated as:
HPCV＝φ×(1-Sw)
where HPCV is the hydrocarbon-containing pore attribute, phi is the porosity, and Sw is the water saturation. The greater the value of the hydrocarbon-containing porosity attribute (HPCV) with increasing porosity and decreasing water saturation (increasing hydrocarbon saturation), the more the distribution of the highly porous hydrocarbon-containing sandstone effective reservoir is characterized.
According to some embodiments of the invention, the expression of the objective function is:
J(x,y)＝corr(F(x,y),HPCV)
wherein J (x, y) is an objective function value, which is a function of undetermined parameters x, y, F (x, y) is a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor, HPCV is a hydrocarbon-containing pore property, and corr is a correlation operation symbol.
According to some embodiments of the invention, the method for obtaining the value of the parameter to be determined in step (4) comprises: and calculating the correlation coefficient of the high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor and the hydrocarbon-bearing pore attribute by utilizing a two-dimensional space parameter scanning method in the two-dimensional space of the x and y parameters, and obtaining the specific values of the undetermined parameters x and y corresponding to the maximum objective function value.
According to some embodiments of the invention, the specific method of reservoir prediction in step (5) comprises: substituting undetermined parameter values obtained by solving the objective function and longitudinal and transverse wave impedance seismic data into a calculation formula of a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor to obtain a discrimination factor seismic data volume; and secondly, obtaining a reservoir prediction threshold according to petrophysical analysis of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors, and comparing the seismic data body obtained by the calculation in the first step with the threshold to predict the reservoir of the researched work area so as to obtain a distribution rule of the high-porosity hydrocarbon-containing sandstone reservoir.
According to some embodiments of the invention, zp is longitudinal wave impedance in g/cm 3 M/s, zs is transverse wave impedance in g/cm 3 M/s, ρ is density in g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s For transverse wave velocity, in m/s, zp=ρ×v p ，Zs＝ρ×v s ，v p /v s ＝Zp/Zs。
According to some embodiments of the invention, the high porosity hydrocarbon-bearing sandstone reservoir discrimination factor petrophysical analysis is characterized by hydrocarbon-bearing pore properties, preferably by porosity and water saturation.
The calculation formula of the hydrocarbon-containing pore properties is as follows: HPCV = phi× (1-Sw), where HPCV is hydrocarbon-containing pore attribute, phi is porosity, sw is water saturation. From this formula, it can be seen that: the higher the porosity, the lower the water saturation, the greater the value of this property and vice versa. The high value of the hydrocarbon-containing pore property corresponds to high porosity and low water saturation, whereas the low value of the hydrocarbon-containing pore property corresponds to low porosity and high water saturation. This hydrocarbon-containing pore property may characterize the reservoir porosity and water saturation. In short, it is the case that the reservoir porosity and water saturation are characterized by the magnitude of this value of the hydrocarbon-containing pore property.
On the other hand, the invention also provides a device for predicting the high-porosity hydrocarbon-containing sandstone reservoir, wherein the device is used for realizing the method for predicting the high-porosity hydrocarbon-containing sandstone reservoir, and the device comprises the following steps: the earthquake and logging data input unit is used for inputting logging curve data of a work area and longitudinal and transverse wave impedance earthquake data; the discrimination factor construction unit is used for constructing a discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir with two-dimensional undetermined parameters based on the input logging curve data; an objective function construction unit for constructing an objective function based on the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors and hydrocarbon-containing pore attributes; the objective function solving unit is used for obtaining undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors by solving the objective function; and the calculating and predicting unit is used for calculating the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor seismic data body according to the undetermined parameter value and carrying out reservoir prediction.
According to some embodiments of the invention, the log data includes longitudinal wave velocity, transverse wave velocity, density, porosity, and water saturation profile.
According to some embodiments of the invention, the longitudinal wave impedance and transverse wave impedance seismic data can be obtained based on pre-stack inversion.
According to some embodiments of the invention, the calculation formula of the high porosity hydrocarbon-containing sandstone reservoir discrimination factor is:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of a high-porosity hydrocarbon-containing sandstone reservoir, is a function of undetermined parameters x, y, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave velocity is given in m/s.
According to some embodiments of the invention, the hydrocarbon-containing pore properties are calculated as:
HPCV＝φ×(1-Sw)
where HPCV is the hydrocarbon-containing pore attribute, phi is the porosity, and Sw is the water saturation.
According to some embodiments of the invention, the expression of the objective function is:
J(x,y)＝corr(F(x,y),HPCV)
wherein J (x, y) is an objective function value, which is a function of undetermined parameters x, y, F (x, y) is a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor, HPCV is a hydrocarbon-containing pore property, and corr is a correlation operation symbol.
According to some embodiments of the invention, the method for obtaining the undetermined parameter value comprises: and calculating the correlation coefficient of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor and the hydrocarbon-containing pore attribute by using a two-dimensional space parameter scanning method to obtain a undetermined parameter value corresponding to the maximum objective function value.
According to some embodiments of the invention, a specific method of performing reservoir prediction comprises: substituting undetermined parameter values obtained by solving the objective function and longitudinal and transverse wave impedance seismic data into a calculation formula of a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor to obtain a discrimination factor seismic data volume; and secondly, obtaining a reservoir prediction threshold value according to petrophysical analysis of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors, and comparing the seismic data body obtained by the calculation in the first step with the threshold value to predict the reservoir of the researched work area.
According to some embodiments of the invention, zp is longitudinal wave impedance in g/cm 3 M/s, zs is transverse wave impedance in units ofg/cm 3 M/s, ρ is density in g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s For transverse wave velocity, in m/s, zp=ρ×v p ，Zs＝ρ×v s ，v p /v s ＝Zp/Zs。
According to some embodiments of the invention, the high pore hydrocarbon-bearing sandstone reservoir discrimination factor petrophysical analysis is characterized by hydrocarbon-bearing pore properties.
Aiming at the exploration of land-phase oil and gas reservoirs in China, the invention provides a high-porosity hydrocarbon-containing sandstone reservoir prediction method, which aims to construct a discrimination attribute factor capable of effectively identifying a high-porosity hydrocarbon-containing sandstone reservoir based on longitudinal and transverse wave speeds and density information, wherein the attribute factor introduces petrophysical constraint in the construction process, and obtains optimal undetermined parameters by solving a two-dimensional parameter space objective function, thereby realizing the best fitting with hydrocarbon-containing pore attributes of the reservoir, effectively ensuring the accuracy of reservoir prediction and reducing exploration risks.
Drawings
FIG. 1 is a flow chart of a method of predicting a highly porous hydrocarbon-bearing sandstone reservoir of the present invention;
FIG. 2 is a flow chart of a high porosity hydrocarbon-bearing sandstone reservoir prediction device of the present invention;
FIG. 3 is a graph showing the distribution of objective functions in a two-dimensional space of undetermined parameters according to embodiment 1 of the present invention;
FIG. 4 is a petrophysical analysis chart of the discrimination factors of the high pore hydrocarbon-bearing sandstone reservoir in the petrophysical prediction template in the embodiment 1 of the present invention;
FIG. 5 is a profile of a hydrocarbon-bearing reservoir distribution predicted from highly porous hydrocarbon-bearing sandstone reservoir discrimination factors, as in example 1 of the present invention.
Detailed Description
The technical solutions 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 will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The embodiment provides a method for predicting a high-porosity hydrocarbon-containing sandstone reservoir (a specific flow is shown in fig. 1), which comprises the following steps:
step 101: and inputting the logging curve data and the longitudinal wave and transverse wave impedance seismic data of the work area.
In practice, the longitudinal and transverse wave impedance seismic data volumes are obtained by conventional pre-stack seismic inversion, and the well log data includes longitudinal wave velocity, transverse wave velocity, density, porosity, and water saturation curves.
Step 102: constructing a high porosity hydrocarbon-bearing sandstone reservoir discrimination factor having two-dimensional undetermined parameters based on the input log data, comprising:
the calculation formula of the discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir is as follows:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir, and is a function of undetermined parameters x, y, x and y are undetermined parameters, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave velocity is given in m/s.
Step 103: constructing an objective function based on the high porosity hydrocarbon-bearing sandstone reservoir discrimination factor and hydrocarbon-bearing pore attributes, comprising:
in the implementation process, firstly, the hydrocarbon-containing pore attribute curve is calculated by using the input porosity and water saturation logging curve and is used for representing the distribution characteristics of the high-porosity hydrocarbon-containing sandstone reservoir, and the calculation formula is as follows:
HPCV＝φ×(1-Sw)
where HPCV is the hydrocarbon-containing pore attribute, phi is the porosity, and Sw is the water saturation. It can be seen that as the porosity increases and the water saturation decreases (the hydrocarbon saturation increases), the value of the hydrocarbon-containing porosity attribute (HPCV) increases, which characterizes the distribution of the highly porous hydrocarbon-containing sandstone effective reservoir.
Then, constructing an objective function based on a correlation analysis method, wherein the expression is as follows:
J(x,y)＝corr(F(x,y),HPCV)
where J (x, y) is the objective function value and corr is the correlation operator. The objective function J (x, y) is a function of the undetermined parameters x and y.
Step 104: solving an objective function by utilizing a two-dimensional space parameter scanning technology to obtain undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors, wherein the method comprises the following steps of:
in the implementation process, the x and y parameters are scanned one by one, and the correlation coefficients of the high-pore hydrocarbon-containing sandstone reservoir discrimination factors and hydrocarbon-containing pore attributes corresponding to different (x, y) parameter combinations are calculated respectively, so that the parameter values of the x and y corresponding to the maximum objective function value are obtained. The specific calculation process comprises the following steps:
firstly, setting the value range of a parameter x to be-50 to 30, the sampling interval to be 1 and the sampling point to be 81; the value range of the parameter y is-5 to 5, the sampling interval is 0.5, and the sampling point is 21; then sequentially fixing the values of the parameter x (for example, when the value of x is 10), and calculating the high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor curves corresponding to all the different y values (namely-5 to 5), wherein the total number of the high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor curves is 21; then the above process is repeated by sequentially changing the value of the parameter x, so that all the discrimination factor curves 1701 (21×81) can be obtained, and each discrimination factor curve corresponds to a different (x, y) parameter combination. And finally, respectively carrying out correlation analysis on the calculated discrimination factor curves and the hydrocarbon-containing pore attribute curves to obtain correlation coefficients (1701) of each discrimination factor curve and the hydrocarbon-containing pore attribute curves. When the correlation coefficient is maximum, the method indicates that the corresponding discrimination factor attribute can best represent the pore development and hydrocarbon content of the reservoir, and can be used for reservoir prediction and fluid detection, and the corresponding x and y parameter values when the maximum correlation coefficient is obtained are the parameter values of the undetermined parameters of the high-pore hydrocarbon-containing sandstone reservoir discrimination factor corresponding to the embodiment. Fig. 3 shows an objective function distribution diagram in two dimensions of undetermined parameters x and y, wherein the abscissa in the figure is an x parameter value, the ordinate is a y parameter value, the dark color represents a region with a large correlation coefficient, the light color represents a region with a small correlation coefficient, it can be seen that the correlation coefficient reaches 0.76 at maximum when the values (-18, -1.5) are taken, and the undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors in the embodiment can be determined to be x= -18, y= -1.5 respectively. Fig. 4 shows a petrophysical analysis chart of the discrimination factors of the high porosity hydrocarbon-containing sandstone reservoir calculated in this example, wherein the abscissa represents porosity and the ordinate represents water saturation, and it can be seen that the low value of the discrimination factor attribute corresponds to the high quality reservoir region (lower right corner) with high porosity and low water saturation. In the research work area, according to the former geological knowledge, when the formation porosity is greater than 0.25 and the water saturation is less than 0.3, the high-quality hydrocarbon-containing reservoir area is identified, and according to the knowledge, the prediction threshold value of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor is F= -1.2 by combining the distribution rule of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor, namely when F < -1.2, the high-porosity hydrocarbon-containing sandstone reservoir area is corresponding, and when F < -1.2, the non-reservoir area or the poor reservoir area is corresponding.
Step 105: calculating a high porosity hydrocarbon-containing sandstone reservoir discrimination factor seismic data volume and performing reservoir prediction, comprising:
in the implementation process, input seismic inversion data and the discrimination factor undetermined parameter value obtained by analysis are substituted into a calculation formula of the discrimination factor of the high-pore hydrocarbon-containing sandstone reservoir to obtain a discrimination factor seismic data body, and then reservoir prediction and fluid detection are carried out by combining a reservoir discrimination factor prediction threshold. The specific calculation process is as follows:
F＝(ρ×v p -18)×(v p /v s -1.5)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Zp＝ρ×v p
Zs＝ρ×v s
v p /v s ＝Zp/Zs
and then an expression for calculating the discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir based on the wave impedance seismic data can be obtained:
F＝(Zp-18)×(Zp/Zs-1.5)
wherein Zp is the input longitudinal wave impedance, zs is the input transverse wave impedance, and F is the calculated high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor.
In an embodiment, the reservoir distribution range based on the calculated high porosity hydrocarbon-bearing sandstone reservoir discrimination factor seismic data volume delineating discrimination factor attribute values below a prediction threshold (-1.2) is a high quality reservoir region of high porosity and low water saturation, while the range above the threshold is considered a non-reservoir or poor reservoir region.
To verify the accuracy of the predicted results, a comparative analysis was performed using the information of the well drilled in the work area, as shown in fig. 5, which is a profile of the distribution of the highly porous hydrocarbon-bearing reservoir predicted from the highly porous hydrocarbon-bearing reservoir discrimination factors, with two wells passing through the profile, wherein the test oil results for the W-1 well at the desired interval (oval dotted line area) were three sets of highly productive hydrocarbon-bearing sandstone reservoirs developed, the test oil results for the W-2 well at the desired interval (oval solid line area) were one set of thin reservoirs developed, and the comprehensive construction and reservoir analysis indicated that the W-2 well test oil was located close to the oil-water interface, resulting in formation water development. In the predicted section shown in fig. 5, the W-1 well corresponds to a low value of the discrimination factor attribute (f= -3.5 or so) at the target interval, and the W-2 well corresponds to a high value of the discrimination factor attribute (f= -0.5 or so), which indicates that the predicted result based on the discrimination factor attribute at the drilled well point is identical to the drilling conclusion, and the effectiveness of the method is verified.
Example 2
The embodiment also provides a device for predicting the high-porosity hydrocarbon-containing sandstone reservoir, which is shown in fig. 2 and comprises:
the earthquake and logging data input unit 201 is used for inputting the logging curve data of the work area and the longitudinal and transverse wave impedance earthquake data; the logging curve data comprise longitudinal wave speed, transverse wave speed, density, porosity and water saturation curves, and longitudinal wave impedance and transverse wave impedance seismic data can be obtained based on pre-stack inversion.
A discrimination factor constructing unit 202 for constructing a discrimination factor of a highly porous hydrocarbon-containing sandstone reservoir with two-dimensional undetermined parameters based on the input log data; the calculation formula of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor is as follows:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of a high-porosity hydrocarbon-containing sandstone reservoir, is a function of undetermined parameters x, y, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave velocity is given in m/s.
An objective function construction unit 203 for constructing an objective function based on the high pore hydrocarbon-containing sandstone reservoir discrimination factors and hydrocarbon-containing pore properties; wherein, the calculation formula of the hydrocarbon-containing pore property is as follows:
HPCV＝φ×(1-Sw)
wherein HPCV is a hydrocarbon-containing pore property,is porosity, sw is water saturation;
the expression of the objective function is:
J(x,y)＝corr(F(x,y),HPCV)
wherein J (x, y) is an objective function value, which is a function of undetermined parameters x, y, F (x, y) is a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor, HPCV is a hydrocarbon-containing pore property, and corr is a correlation operation symbol.
An objective function solving unit 204, configured to obtain a value of a parameter to be determined in the high-pore hydrocarbon-containing sandstone reservoir discrimination factor by solving the objective function; the method for acquiring the undetermined parameter value comprises the following steps: and calculating the correlation coefficient of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor and the hydrocarbon-containing pore attribute by using a two-dimensional space parameter scanning method to obtain a undetermined parameter value corresponding to the maximum objective function value.
The calculating and predicting unit 205 is configured to calculate a high-pore hydrocarbon-bearing sandstone reservoir discrimination factor seismic data body according to the undetermined parameter value and the longitudinal wave impedance seismic data, and perform reservoir prediction; the method for carrying out reservoir prediction specifically comprises the following steps: substituting undetermined parameter values obtained by solving the objective function and longitudinal and transverse wave impedance seismic data into a calculation formula of a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor to obtain a discrimination factor seismic data volume; second, according to the heightRock physical analysis of the porous hydrocarbon-containing sandstone reservoir discrimination factors is carried out to obtain a reservoir prediction threshold value, and the seismic data volume obtained by the calculation in the first step is compared with the threshold value so as to carry out reservoir prediction on a researched work area; zp is longitudinal wave impedance, zs is transverse wave impedance, ρ is density, v p For longitudinal wave velocity, v s Zp=ρ×v for transverse wave velocity p ，Zs＝ρ×v s ，v p /v s =zp/Zs; the petrophysical analysis of the high porosity hydrocarbon-bearing sandstone reservoir discrimination factor is characterized by hydrocarbon-bearing pore properties.
The foregoing description of the embodiments of the present invention further provides the objects, technical solutions and advantages of the present invention, and it should be understood that the foregoing description is only illustrative of the embodiments of the present invention and is not intended to limit the scope of the present invention, and any modifications or equivalent substitutions made without departing from the spirit and scope of the present invention and modifications thereof should be covered by the scope of the claims of the present invention.
Claims (7)
1. A method of predicting a highly porous hydrocarbon-bearing sandstone reservoir, wherein the method comprises:
(1) Acquiring well logging curve data and longitudinal and transverse wave impedance seismic data of a work area; wherein the log data comprises a compressional velocity, a shear velocity, a density, a porosity, and a water saturation curve;
(2) Constructing a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor with two-dimensional undetermined parameters based on the logging curve data obtained in the step (1); the calculation formula of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor is as follows:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of a high-porosity hydrocarbon-containing sandstone reservoir, is a function of undetermined parameters x, y, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave speed is m/s;
(3) Constructing an objective function based on the hydrocarbon-containing pore attributes and the high-pore hydrocarbon-containing sandstone reservoir discrimination factors obtained in the step (2); wherein, the calculation formula of the hydrocarbon-containing pore property is as follows:
HPCV＝φ×(1-Sw)
wherein HPCV is the hydrocarbon-containing pore property, phi is the porosity, sw is the water saturation;
(4) Solving the objective function to obtain undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors; wherein, the expression of the objective function is:
J(x,y)＝corr(F(x,y),HPCV)
wherein J (x, y) is an objective function value, is a function of undetermined parameters x, y, F (x, y) is a high-pore hydrocarbon-containing sandstone reservoir discrimination factor, HPCV is a hydrocarbon-containing pore property, and corr is a related operation symbol;
(5) And (3) calculating a high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor seismic data body according to the undetermined parameter value and the longitudinal wave impedance seismic data in the step (1) and carrying out reservoir prediction.
2. The method of claim 1, wherein the longitudinal and transverse wave impedance seismic data is obtainable based on pre-stack inversion.
3. The method according to claim 1 or 2, wherein the method for obtaining the value of the parameter to be determined in step (4) comprises: and calculating the correlation coefficient of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor and the hydrocarbon-containing pore attribute by using a two-dimensional space parameter scanning method to obtain a undetermined parameter value corresponding to the maximum objective function value.
4. The method of claim 1 or 2, wherein the specific method of reservoir prediction in step (5) comprises:
substituting undetermined parameter values obtained by solving the objective function and longitudinal and transverse wave impedance seismic data into a calculation formula of a high-porosity hydrocarbon-containing sandstone reservoir discrimination factor to obtain a discrimination factor seismic data volume;
and secondly, obtaining a reservoir prediction threshold value according to petrophysical analysis of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors, and comparing the seismic data body obtained by the calculation in the first step with the threshold value to predict the reservoir of the researched work area.
5. The method of claim 4, wherein Zp is longitudinal wave impedance in g/cm 3 M/s, zs is transverse wave impedance in g/cm 3 M/s, ρ is density in g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s For transverse wave velocity, in m/s, zp=ρ×v p ，Zs＝ρ×v s ，v p /v s ＝Zp/Zs。
6. The method of claim 4, wherein the high pore hydrocarbon-bearing sandstone reservoir discrimination factor petrophysical analysis is characterized by hydrocarbon-bearing pore properties.
7. A high porosity hydrocarbon-bearing sandstone reservoir prediction device, wherein the device is configured to implement the high porosity hydrocarbon-bearing sandstone reservoir prediction method of any of claims 1 to 6, comprising:
the earthquake and logging data input unit is used for inputting logging curve data of a work area and longitudinal and transverse wave impedance earthquake data; wherein the log data comprises a compressional velocity, a shear velocity, a density, a porosity, and a water saturation curve;
the discrimination factor construction unit is used for constructing a discrimination factor of the high-porosity hydrocarbon-containing sandstone reservoir with two-dimensional undetermined parameters based on the input logging curve data; the calculation formula of the high-porosity hydrocarbon-containing sandstone reservoir discrimination factor is as follows:
F(x,y)＝(ρ×v p +x)×(v p /v s +y)
wherein F (x, y) is a discrimination factor of a high-porosity hydrocarbon-containing sandstone reservoir, is a function of undetermined parameters x, y, ρ is density, and the unit is g/cm 3 ，v p Is the longitudinal wave velocity, the unit is m/s, v s The transverse wave speed is m/s;
an objective function construction unit for constructing an objective function based on the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors and hydrocarbon-containing pore attributes; wherein, the calculation formula of the hydrocarbon-containing pore property is as follows:
HPCV＝φ×(1-Sw)
wherein HPCV is the hydrocarbon-containing pore property, phi is the porosity, sw is the water saturation;
the objective function solving unit is used for obtaining undetermined parameter values in the high-porosity hydrocarbon-containing sandstone reservoir discrimination factors by solving the objective function; wherein, the expression of the objective function is:
J(x,y)＝corr(F(x,y),HPCV)
wherein J (x, y) is an objective function value, is a function of undetermined parameters x, y, F (x, y) is a high-pore hydrocarbon-containing sandstone reservoir discrimination factor, HPCV is a hydrocarbon-containing pore property, and corr is a related operation symbol;
and the calculating and predicting unit is used for calculating a high-porosity hydrocarbon-bearing sandstone reservoir discrimination factor seismic data body according to the undetermined parameter value and the longitudinal wave and transverse wave impedance seismic data and predicting the reservoir.
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