CN111381292A - Logging interpretation method and device for predicting sandstone hydrocarbon-bearing reservoir - Google Patents
Logging interpretation method and device for predicting sandstone hydrocarbon-bearing reservoir Download PDFInfo
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Abstract
The invention provides a logging interpretation method and a logging interpretation device for predicting a sandstone hydrocarbon-bearing reservoir. The method comprises the following steps: obtaining physical property parameters of a rock matrix and logging curve data; calculating longitudinal wave velocity, transverse wave velocity and density based on the physical property parameters of the rock matrix; constructing a sandstone hydrocarbon-bearing reservoir prediction factor, wherein the expression of the prediction factor comprises longitudinal wave velocity, transverse wave velocity and density; calculating and analyzing distribution characteristics of prediction factors of the sandstone hydrocarbon-bearing reservoir based on compressional wave velocity, shear wave velocity and density, and determining a prediction threshold value of the sandstone hydrocarbon-bearing reservoir; and calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data, and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold value. The device comprises: the device comprises a data acquisition unit, a speed density calculation unit, a sandstone hydrocarbon-bearing reservoir prediction factor construction unit, a hydrocarbon-bearing reservoir prediction threshold analysis unit and a sandstone hydrocarbon-bearing reservoir prediction unit. The method overcomes the singleness and the multiplicity of the fluid prediction only by resistivity information.
Description
Technical Field
The invention belongs to the field of geophysical exploration of petroleum, and relates to a logging interpretation method and a logging interpretation device for predicting sandstone hydrocarbon-bearing reservoirs.
Background
In the exploration and development of petroleum and natural gas, a logging curve obtained by a logging instrument directly reflects the physical properties of the rock of the stratum around the well. With the continuous progress of well logging technology, various characteristic curves for representing the physical properties, electrical properties and fluid properties of rocks can be obtained by conventional well logging, wherein the characteristic curves comprise a longitudinal wave acoustic curve, a transverse wave acoustic curve, a density curve, a GR curve, a depth resistivity curve, a neutron porosity curve and the like. With the continuous deepening of subject fusion, the combination of earthquake, well logging and geology is more compact, so that the characteristic technology originally applied to other fields is widely applied to the well logging interpretation field, as is well known, the acquisition and processing of earthquake data depend on and reflect the physical properties of underground rocks, and the acoustic curve and the density curve in well logging are also used for observing the physical properties of rocks around the underground well, and have physical consistency with the underground rocks, but the two are obviously different due to the difference of observation means and are mainly shown in the aspects of scale, frequency, measurement precision and the like. Seismic rock physical theory analysis considers that information such as longitudinal and transverse wave velocity, density and the like can effectively judge the fluid-containing property of a reservoir, in the seismic field, the longitudinal and transverse wave impedance and density are generally obtained by using a pre-stack seismic inversion technology, attribute factors for representing reservoir fluid are constructed on the basis of the longitudinal and transverse wave impedance and density information, and finally hydrocarbon-containing favorable areas of the reservoir are identified through the fluid attribute factors, in the logging field, hydrocarbon-containing reservoir prediction methods based on velocity and density are rare, the main reason is that a resistivity curve in logging can represent and identify the reservoir fluid on the basis of electrical information, prediction of hydrocarbon-containing reservoirs around the well is realized to a certain extent, and the other reason is that the early conventional logging technology is limited by cost and technical requirements, transverse wave logging information can be rarely obtained, and transverse waves have natural sensitivity to the reservoir fluid, and therefore, reservoir fluid prediction based on the physical properties of rocks such as speed, density and the like is difficult to carry out under the condition of lacking transverse waves. With the development of the rock physics theory and the progress of the logging acquisition technology, transverse wave measurement and prediction are solved to a great extent, so that accurate and reliable transverse wave information can be obtained, and meanwhile, the research on a method for predicting the hydrocarbon distribution around a logging well based on physical property information such as sound waves and density is promoted.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a logging interpretation method for predicting a sandstone hydrocarbon-containing reservoir, which fully utilizes longitudinal and transverse waves and density information to realize logging interpretation of the sandstone hydrocarbon-containing reservoir, overcomes the singleness and the multiple solution of the conventional method for predicting fluid only by using resistivity information, realizes logging interpretation of the sandstone hydrocarbon-containing reservoir based on physical property characteristics, provides a reliable technical means for predicting the hydrocarbon-containing reservoir by using a conventional logging curve, and improves the accuracy of reservoir prediction.
In order to achieve the above object, the present invention provides a well logging interpretation method for predicting sandstone hydrocarbon-bearing reservoirs, the method comprising:
1) obtaining physical property parameters of a rock matrix and logging curve data;
2) calculating longitudinal wave velocity, transverse wave velocity and density of the sandstone reservoir saturated with different fluids based on the physical parameters of the rock matrix obtained in the step 1);
3) constructing a sandstone hydrocarbon-bearing reservoir prediction factor, wherein the expression of the sandstone hydrocarbon-bearing reservoir prediction factor comprises longitudinal wave velocity, transverse wave velocity and density;
4) calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir which are obtained by calculation in the step 2) when the sandstone reservoir is saturated with different fluids, and determining the sandstone hydrocarbon-bearing reservoir prediction threshold;
5) calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data obtained in the step 1) and the hydrocarbon-bearing reservoir prediction factor constructed in the step 3), and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold value determined in the step 4).
In the above well logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, preferably, the rock matrix property parameters include: rock matrix bulk modulus (i.e., solid matrix bulk modulus), rock skeleton bulk modulus, shear modulus, density, porosity of the rock skeleton, and bulk modulus of the mixed fluid (i.e., pore hydrocarbon containing bulk modulus), fluid viscosity, permeability, media thickness, and the like. In order to more accurately realize the prediction of the sandstone hydrocarbon-bearing reservoir, the generally selected rock matrix physical property parameters need to be selected to represent the rock matrix physical property parameters of the region to be predicted; for example, the rock matrix property parameters of exploration wells, evaluation wells, etc. with prediction regions may be selected.
In the logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir described above, preferably, the logging curve data includes a compressional velocity curve, a shear velocity curve, a density curve, and a neutron porosity curve.
In the logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, preferably, in the step 2), the calculation of the longitudinal and transverse wave velocities and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids is carried out by using a sandstone White model; more preferably, the calculating of the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids based on the rock matrix physical property parameters obtained in the step 1) comprises: A. calculating the elastic modulus of the fluid saturated medium by using a sandstone White model based on the physical property parameters of the rock matrix; B. calculating the longitudinal wave velocity, the transverse wave velocity and the density by utilizing a sandstone White model based on the physical property parameters of the rock matrix and the elastic modulus of the fluid saturated medium; the formula for calculating the elastic modulus of the fluid saturated medium is preferably as follows:
wherein the content of the first and second substances,
wherein E is the modulus of elasticity of the fluid saturated medium, E0Is the modulus of elasticity, K, of dry rockmIs the bulk modulus of the rock skeleton, KgIs the bulk modulus of the rock matrix, KfFor mixed fluid bulk modulus, μmIs the shear modulus of the rock skeleton,
is porosity, p is the ratio of the first fluid and the second fluid saturation, p1Saturation of the containing fluid one (i.e. containing the upper fluid), p2Saturation of fluid two (i.e. lower layer containing fluid), η is flowThe coefficient of bulk viscosity, kappa is permeability, k is complex wave number of longitudinal wave, d is medium thickness, i is imaginary unit, and omega is angular frequency; wherein the density of the first fluid is lower than the density of the second fluid and ar represents the change in internal stress of the rock. Specifically, when a seismic wave passes through a pore medium saturated with fluid, pore fluid flows due to pore pressure imbalance, and the flow causes stress distribution changes in the rock, and the stress changes caused by the fluid flow can be characterized by Δ r.
The formula for calculating the velocity of longitudinal waves, the velocity of transverse waves and the density is preferably as follows:
wherein the density of the medium of the saturated fluid I (i.e. the upper medium) is rho1The density of the medium of the saturated fluid two (i.e., the lower medium) is ρ2The saturation of the fluid containing one (i.e. the upper fluid) is p1With the saturation of the fluid two (i.e. the fluid containing the lower layer) being p2Sandstone longitudinal wave velocity (i.e. the velocity of the longitudinal wave) is vpThe sandstone transverse wave velocity (namely the transverse wave velocity) is vsThe density of the tri-sandstone (i.e. the density) is ρd(ii) a Wherein the density of the first saturated fluid is lower than the density of the second saturated fluid.
The White model is a two-phase medium theoretical model distributed in a mutual layer mode and consists of two saturated fluid media, in the process of calculating by using the White model, the sum of the saturation of the upper fluid (namely the fluid I) and the saturation of the lower fluid (namely the fluid II) is 1, the upper medium is a reservoir saturated with the upper fluid, and the lower medium is a reservoir saturated with the lower fluid.
In the logging interpretation method for predicting the sandstone hydrocarbon-bearing reservoir, preferably, the expression of the sandstone hydrocarbon-bearing reservoir prediction factor is
Wherein F is sandstone hydrocarbon-bearing reservoir prediction factor vpIs the sandstone longitudinal wave velocity (i.e. the longitudinal wave velocity), vsIs the sandstone shear wave velocity (i.e. the shear wave velocity), pdIs the density of the sand (i.e. the density),
is porosity.
In the logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, specifically, the calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factor when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir, which are calculated in the step 2), and determining the sandstone hydrocarbon-bearing reservoir prediction threshold value may be performed by a method including the following steps: respectively substituting the calculated compressional wave velocity, shear wave velocity and density of the sandstone reservoir saturated with different fluids into a sandstone hydrocarbon-bearing reservoir prediction factor formula to respectively obtain the distribution characteristics of hydrocarbon-bearing reservoir prediction factors of the sandstone reservoir saturated with different fluids, and determining a sandstone hydrocarbon-bearing reservoir prediction threshold value by analyzing the distribution characteristics of the hydrocarbon-bearing reservoir prediction factors of the sandstone reservoir saturated with different fluids, wherein the sandstone hydrocarbon-bearing reservoir prediction threshold value can eliminate the influence of a water layer to determine the distribution range of the sandstone hydrocarbon-bearing reservoir; preferably, the analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids and the determining the sandstone hydrocarbon-bearing reservoir prediction threshold are realized by respectively performing petrophysical template and sensitivity analysis on the hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids and determining the sandstone hydrocarbon-bearing reservoir prediction threshold.
In the above well interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, preferably, the saturated different fluids include saturated water, saturated oil and saturated gas.
In the logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, preferably, in step 5), the step of calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data obtained in step 1) and the hydrocarbon-bearing reservoir prediction factor constructed in step 3), and the step of predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold determined in step 4) includes: substituting the acquired logging curve data into a sandstone hydrocarbon-bearing reservoir prediction factor formula to obtain a hydrocarbon-bearing reservoir prediction factor curve, and then judging according to a hydrocarbon-bearing reservoir prediction threshold value: and the curve part of the hydrocarbon-bearing reservoir prediction factor which is greater than or equal to the threshold value is a hydrocarbon-bearing reservoir, and the curve part which is smaller than the threshold value is an aquifer or a compact layer, so that the identification of the sandstone hydrocarbon-bearing reservoir is realized.
The invention also provides an apparatus for predicting a sandstone hydrocarbon-bearing reservoir, the apparatus comprising:
the data acquisition unit is used for acquiring physical property parameters of the rock matrix and logging curve data; the obtained physical property parameters of the rock matrix are transmitted to a speed density calculation unit, and the obtained logging curve data are transmitted to a sandstone hydrocarbon-bearing reservoir prediction unit;
the velocity density calculation unit is used for calculating the longitudinal wave velocity, the transverse wave velocity and the density of the sandstone reservoir when different fluids are saturated on the basis of the physical parameters of the rock matrix acquired by the data acquisition unit; the calculated compressional wave velocity, shear wave velocity and density of the saturated sandstone reservoir with different fluids are transmitted to a hydrocarbon-bearing reservoir prediction threshold analysis unit;
the sandstone hydrocarbon-bearing reservoir prediction factor construction unit is used for constructing sandstone hydrocarbon-bearing reservoir prediction factors, wherein the expressions of the sandstone hydrocarbon-bearing reservoir prediction factors comprise longitudinal wave velocity, transverse wave velocity and density; the constructed sandstone hydrocarbon-bearing reservoir prediction factors are respectively transmitted to a hydrocarbon-bearing reservoir prediction threshold analysis unit and a sandstone hydrocarbon-bearing reservoir prediction unit;
the hydrocarbon-bearing reservoir prediction threshold analysis unit is used for calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids, which are calculated by the velocity density calculation unit, and the sandstone hydrocarbon-bearing reservoir prediction factors constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit, and determining the sandstone hydrocarbon-bearing reservoir prediction threshold; determining the obtained sandstone hydrocarbon-bearing reservoir prediction threshold value, and transmitting the sandstone hydrocarbon-bearing reservoir prediction threshold value to a sandstone hydrocarbon-bearing reservoir prediction unit;
and the sandstone hydrocarbon-bearing reservoir prediction unit is used for calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data acquired by the data acquisition unit and the sandstone hydrocarbon-bearing reservoir prediction factor constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold determined by the hydrocarbon-bearing reservoir prediction threshold analysis unit.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, preferably, the rock matrix property parameter includes: rock matrix bulk modulus (i.e., solid matrix bulk modulus), rock skeleton bulk modulus, rock skeleton shear modulus, density, porosity, and mixed fluid bulk modulus, fluid viscosity coefficient, permeability, media thickness, and the like.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, preferably, the log data includes a compressional velocity profile, a shear velocity profile, a density profile, and a neutron porosity profile.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, preferably, in the velocity density calculation unit, the calculation of the compressional-compressional velocity and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids is performed by using a sandstone White model; more preferably, the calculating of the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids based on the rock matrix physical property parameters obtained in the step 1) comprises: A. calculating the elastic modulus of the fluid saturated medium by using a sandstone White model based on the physical property parameters of the rock matrix; B. calculating the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when different fluids are saturated by utilizing a sandstone White model based on the physical property parameters of the rock matrix and the elastic modulus of a fluid saturated medium; the formula for calculating the elastic modulus of the fluid saturated medium is preferably as follows:
wherein the content of the first and second substances,
wherein E is the modulus of elasticity of the fluid saturated medium, E0Is the modulus of elasticity, K, of dry rockmIs the bulk modulus of the rock skeleton, KgIs the bulk modulus of the rock matrix, KfFor mixed fluid bulk modulus, μmIs the shear modulus of the rock skeleton,
is porosity, p is the ratio of the first fluid and the second fluid saturation, p1Saturation of the containing fluid one (i.e. containing the upper fluid), p2Specifically, when the seismic wave passes through the pore medium of the saturated fluid, pore fluid flows due to unbalanced pore pressure, the stress distribution in the rock changes due to the flow, and the stress change caused by the fluid flow can be characterized by delta r.
The formula for calculating the velocity of longitudinal waves, the velocity of transverse waves and the density is preferably as follows:
wherein the density of the medium of the saturated fluid I (i.e. the upper medium) is rho1The density of the medium of the saturated fluid two (i.e., the lower medium) is ρ2The saturation of the fluid containing one (i.e. the upper fluid) is p1With the saturation of the fluid two (i.e. the fluid containing the lower layer) being p2Sandstone longitudinal wave velocity (i.e. the velocity of the longitudinal wave) is vpThe sandstone transverse wave velocity (namely the transverse wave velocity) is vsThe density of the tri-sandstone (i.e. the density) is ρd(ii) a Wherein the density of the first saturated fluid is lower than the density of the second saturated fluid.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, preferably, in the unit for constructing a sandstone hydrocarbon-bearing reservoir prediction factor, the expression of the sandstone hydrocarbon-bearing reservoir prediction factor is
Wherein F is sandstone hydrocarbon-bearing reservoir prediction factor vpIs the sandstone longitudinal wave velocity (i.e. the longitudinal wave velocity), vsIs the sandstone shear wave velocity (i.e. the shear wave velocity), pdIs the density of the sand (i.e. the density),
is porosity.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, specifically, in the hydrocarbon-bearing reservoir prediction threshold analysis unit, the determining a sandstone hydrocarbon-bearing reservoir prediction threshold value may be performed by calculating and analyzing distribution characteristics of sandstone hydrocarbon-bearing reservoir prediction factors of the sandstone reservoir when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity, and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids, which are calculated in step 2), and by: substituting the calculated compressional wave velocity, shear wave velocity and density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids into a sandstone hydrocarbon-bearing reservoir prediction factor formula to respectively obtain the distribution characteristics of hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids, and determining a sandstone hydrocarbon-bearing reservoir prediction threshold value by analyzing the hydrocarbon-bearing reservoir prediction factor distribution characteristics when the sandstone reservoir is saturated with different fluids, wherein the sandstone hydrocarbon-bearing reservoir prediction threshold value can eliminate the influence of a water layer to determine the distribution range of the sandstone hydrocarbon-bearing reservoir.
In the above apparatus for predicting a sandstone hydrocarbon-bearing reservoir, preferably, the saturated different fluids include saturated water, saturated oil and saturated gas.
In the above apparatus for predicting a sandstone hydrocarbon-containing reservoir, preferably, in the sandstone hydrocarbon-containing reservoir prediction unit, the calculating a sandstone hydrocarbon-containing reservoir prediction factor curve using the logging curve data acquired by the data acquisition unit and the sandstone hydrocarbon-containing reservoir prediction factor constructed by the sandstone hydrocarbon-containing reservoir prediction factor construction unit, and the predicting a hydrocarbon-containing reservoir according to the sandstone hydrocarbon-containing reservoir prediction threshold determined by the hydrocarbon-containing reservoir prediction threshold analysis unit includes: substituting the acquired logging curve data into a sandstone hydrocarbon-bearing reservoir prediction factor formula to obtain a hydrocarbon-bearing reservoir prediction factor curve, and then judging according to a hydrocarbon-bearing reservoir prediction threshold value: and the curve part of the hydrocarbon-bearing reservoir prediction factor which is greater than or equal to the threshold value is a hydrocarbon-bearing reservoir, and the curve part which is smaller than the threshold value is an aquifer or a compact layer, so that the identification of the sandstone hydrocarbon-bearing reservoir is realized.
The logging interpretation method for predicting the sandstone hydrocarbon-bearing reservoir provided by the invention is used for obtaining the well cycle longitudinal wave velocity, the shear wave velocity and the density by calculation based on the physical property parameters of the rock matrix, calculating and analyzing the distribution characteristics of the prediction factors of the sandstone hydrocarbon-bearing reservoir according to the constructed prediction factor formula of the sandstone hydrocarbon-bearing reservoir and determining the prediction threshold value of the sandstone hydrocarbon-bearing reservoir, and finally calculating the prediction factor curve of the sandstone hydrocarbon-bearing reservoir by using the logging curve and carrying out fluid detection according to the prediction threshold value of the sandstone hydrocarbon-bearing reservoir. The method fully utilizes the longitudinal and transverse waves and the density information to realize the logging interpretation of the sandstone hydrocarbon-bearing reservoir, overcomes the singleness and the multiple solution of the conventional method for predicting the fluid only by the resistivity information, realizes the logging interpretation of the sandstone hydrocarbon-bearing reservoir based on the physical property characteristics, provides a reliable technical means for predicting the hydrocarbon-bearing reservoir by using the conventional logging curve, and improves the accuracy of reservoir prediction.
Drawings
Fig. 1 is a flow chart of a well logging interpretation method for predicting sandstone hydrocarbon-bearing reservoirs in example 1.
FIG. 2A is a plot of the log data obtained in example 1.
Fig. 2B is a graph of the transverse wave velocity and the longitudinal wave velocity in the states of saturated water, saturated oil, and saturated gas calculated in example 1.
Fig. 2C is a density map in a state of saturated water, saturated oil, and saturated gas calculated in example 1.
Figure 3 is a sandstone reservoir hydrocarbon-bearing fluid factor profile constructed in example 1.
Figure 4 is a profile of sandstone hydrocarbon-bearing reservoir fluid factor in a petrophysical template constructed in example 1.
Fig. 5 is a diagram of fluid factor curves and well logging interpretation results of sandstone hydrocarbon-bearing reservoirs calculated in example 1.
Detailed Description
The technical solutions of the present invention will be described in detail below in order to clearly understand the technical features, objects, and advantages of the present invention, but the present invention is not limited to the practical scope of the present invention.
Example 1
The present embodiment provides a well logging interpretation method for predicting sandstone hydrocarbon-bearing reservoirs (the process is shown in fig. 1), which includes:
1) obtaining physical property parameters of rock matrixes in a work area and logging curve data; wherein the rock matrix physical property parameters include: rock matrix bulk modulus, rock skeleton bulk modulus, shear modulus, density, porosity of rock skeleton, mixed fluid bulk modulus, fluid viscosity coefficient, permeability, and medium thickness; the logging curve data comprises a longitudinal wave velocity curve, a transverse wave velocity curve, a density curve and a neutron porosity curve; specific data are shown in table 1 and fig. 2A.
TABLE 1
2) Based on the physical property parameters of the rock matrix obtained in the step 1), respectively calculating the longitudinal wave velocity, the transverse wave velocity and the density of saturated water, saturated oil and saturated gas by using a sandstone White model; the specific process is as follows:
A. calculating the elastic modulus of the fluid saturated medium by using a sandstone White model based on the physical property parameters of the rock matrix; the specific calculation formula is as follows:
wherein the content of the first and second substances,
wherein E is the modulus of elasticity of the fluid saturated medium, E0Is the modulus of elasticity, K, of dry rockmIs the bulk modulus of the rock skeleton, KgIs the bulk modulus of the rock matrix, KfFor mixed fluid bulk modulus, μmIs the shear modulus of the rock skeleton,
is porosity, p is the ratio of the first fluid and the second fluid saturation, p1Is a fluid-containing one degree of saturation, p2And the saturation degree of the fluid II is η, the viscosity coefficient of the fluid is η, kappa is the permeability, k is the complex wave number of the longitudinal wave, d is the thickness of the medium, i is an imaginary number unit, and omega is the angular frequency, wherein the density of the fluid I is lower than that of the fluid II, and deltar represents the change of the internal stress of the rock.
B. Calculating the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when different fluids are saturated by utilizing a sandstone White model based on the physical property parameters of the rock matrix and the elastic modulus of a fluid saturated medium; the specific calculation formula is as follows:
wherein the density of the medium of the saturated fluid I (i.e. the upper medium) is rho1The density of the medium of the saturated fluid two (i.e., the lower medium) is ρ2The saturation of the fluid containing one (i.e. the upper fluid) is p1With the saturation of the fluid two (i.e. the fluid containing the lower layer) being p2Sandstone longitudinal wave velocity (i.e. the velocity of the longitudinal wave) is vpThe sandstone transverse wave velocity (namely the transverse wave velocity) is vsThe density of the tri-sandstone (i.e. the density) is ρd(ii) a Wherein the density of the saturated fluid one is lower than that of the saturated fluid two;
the calculated longitudinal wave velocity, transverse wave velocity, and density are shown in fig. 2B and 2C.
3) Constructing a sandstone hydrocarbon-bearing reservoir prediction factor, wherein the expression of the sandstone hydrocarbon-bearing reservoir prediction factor comprises longitudinal wave velocity, transverse wave velocity and density; the specific construction process is as follows:
according to the Mavko approximation formula, the viscoelastic fracture medium fluid identification property is expressed as:
when the fractured medium is approximated as a sandstone pore medium, the fracture density is expressed as:
meanwhile, for a viscoelastic porous medium, the following approximate formula is shown:
derived, attribute SQ is identified from the fracture medium fluidpThe sandstone pore medium fluid identification attribute can be obtained, namely the expression of the sandstone hydrocarbon-bearing reservoir prediction factor F is：
Wherein epsilon is fracture density, M is compression bulk modulus, G is shear bulk modulus, SQp is fracture medium fluid identification attribute, F is sandstone hydrocarbon-bearing reservoir prediction factor, and ν ispIs sandstone longitudinal wave velocity, vsIs the sandstone shear wave velocity, rhodIs the density of the sandstone and the sand is,
is porosity.
4) Calculating and analyzing the distribution characteristics of the prediction factors of the sandstone hydrocarbon-bearing reservoir when the saturated water, the saturated oil and the saturated gas are obtained on the basis of the longitudinal wave velocity, the transverse wave velocity and the density when the saturated water, the saturated oil and the saturated gas are obtained by calculation in the step 2), and determining the prediction threshold value of the sandstone hydrocarbon-bearing reservoir; the specific process comprises the following steps:
A. respectively substituting the calculated longitudinal wave velocity, transverse wave velocity and density of saturated water, saturated oil and saturated gas into a sandstone hydrocarbon-bearing reservoir prediction factor formula to respectively obtain distribution characteristics (and values of the prediction factors) of the prediction factors when different fluids (saturated water, saturated oil and saturated gas) are saturated;
B. determining a sandstone hydrocarbon-bearing reservoir prediction threshold value by respectively carrying out petrophysical template and sensitivity analysis on prediction factors of different saturated fluids, wherein the sandstone hydrocarbon-bearing reservoir prediction threshold value can eliminate the influence of a water layer to determine the distribution range of the sandstone hydrocarbon-bearing reservoir;
specifically, a prediction factor sensitivity analysis graph (shown in fig. 3) is firstly drawn, in fig. 4, the abscissa represents porosity, and the ordinate represents hydrocarbon-bearing reservoir prediction factor F, wherein a black solid line represents a saturation waterline, and black dotted lines represent a saturation oil line and a saturation gas line, respectively, when F is greater than or equal to 0.067, namely a dark area part, the hydrocarbon-bearing reservoir prediction factor indicates a hydrocarbon-bearing (oil and gas) reservoir distribution area, and no change is concluded no matter how the reservoir porosity changes; when F <0.067, the hydrocarbon-bearing reservoir predictor indicates an aquifer distribution region, and the distribution law does not change with porosity; the hydrocarbon-bearing reservoir prediction factor can effectively distinguish the hydrocarbon-bearing reservoir from the water layer, and the application effect is not influenced by the porosity;
further, a hydrocarbon-bearing reservoir prediction factor distribution rule is analyzed based on a petrophysical template (shown in fig. 4), wherein colors in the diagram represent the attribute sizes of the hydrocarbon-bearing reservoir prediction factors, a lower left dark region (a dotted oval region) represents a saturated gas reservoir, and an upper right region (a solid oval region) represents a saturated water reservoir, so that the hydrocarbon-bearing reservoir prediction factors can effectively distinguish the hydrocarbon-bearing reservoir from a water layer;
finally, the predicted threshold value of the sandstone hydrocarbon-bearing reservoir is determined to be 0.067.
5) Calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data obtained in the step 1) and the hydrocarbon-bearing reservoir prediction factor constructed in the step 3), and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold value determined in the step 4); specifically, the method comprises the following steps:
substituting the acquired logging curve data into a sandstone hydrocarbon-bearing reservoir prediction factor formula to obtain a hydrocarbon-bearing reservoir prediction factor curve (as shown in the left side of fig. 5), and then judging according to a hydrocarbon-bearing reservoir prediction threshold value: the curve part of the hydrocarbon-bearing reservoir prediction factor which is greater than or equal to the threshold value is a hydrocarbon-bearing reservoir, and the curve part which is smaller than the threshold value is an aquifer or a compact layer, so that the sandstone hydrocarbon-bearing reservoir is identified; in the figure, the abscissa is the attribute amplitude value of the hydrocarbon-bearing reservoir prediction factor, the ordinate is the depth, and a black dotted line represents an isoline when the reservoir prediction factor F is 0.067, it can be seen that the value of the hydrocarbon-bearing reservoir prediction factor is obviously increased between the depths of 2150 and 2200 meters, which indicates that the hydrocarbon-bearing reservoir develops a gas-bearing reservoir in the depth section, similarly, the value of the hydrocarbon-bearing reservoir prediction factor is moderately larger between the depths of 2200 and 2250 meters, which indicates that the depth section develops a set of oil layers, and the value of the hydrocarbon-bearing reservoir prediction factor fluctuates but is slightly smaller around 2050 meters, which indicates that the water layer develops in the depth section.
In order to verify the reliability of the logging interpretation method for predicting the sandstone hydrocarbon-containing reservoir, oil testing is carried out on the oil field of the three depth sections, the oil testing result is shown on the right side of fig. 5, and the oil testing result is proved to be consistent with the prediction result of the sandstone hydrocarbon-containing reservoir prediction factor, which indicates that the logging interpretation method for predicting the sandstone hydrocarbon-containing reservoir disclosed by the invention is effective and reliable.
The embodiment also provides a device for predicting a sandstone hydrocarbon-containing reservoir, which is used for implementing the logging interpretation method for predicting the sandstone hydrocarbon-containing reservoir, wherein the device comprises:
the data acquisition unit is used for acquiring physical property parameters of rock matrixes in a work area and logging curve data, transmitting the physical property parameters of the rock matrixes to the speed density calculation unit and transmitting the logging curve data to the sandstone hydrocarbon-bearing reservoir prediction unit; wherein the rock matrix physical property parameters include: rock matrix bulk modulus, rock skeleton bulk modulus, shear modulus, density, porosity of rock skeleton, mixed fluid bulk modulus, fluid viscosity coefficient, permeability, and medium thickness; the log data includes a compressional velocity profile, a shear velocity profile, a density profile, and a neutron porosity profile.
The velocity density calculation unit is connected with the data acquisition unit and used for calculating the compressional wave velocity, the shear wave velocity and the density of saturated water, saturated oil and saturated gas by utilizing a sandstone White model based on the physical parameters of the rock matrix, and transmitting the compressional wave velocity, the shear wave velocity and the density of the saturated water, the saturated oil and the saturated gas to the hydrocarbon-bearing reservoir prediction threshold analysis unit; the method for calculating the longitudinal wave velocity, the transverse wave velocity and the density of saturated water, saturated oil and saturated gas by using the sandstone White model based on the physical property parameters of the rock matrix comprises the following steps:
A. and calculating the elastic modulus of the fluid saturated medium by using a sandstone White model based on the physical property parameters of the rock matrix, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
e is the modulus of elasticity of the fluid saturated medium, E0Is the modulus of elasticity, K, of dry rockmIs the bulk modulus of the rock skeleton, KgIs the bulk modulus of the rock matrix, KfFor mixed fluid bulk modulus, μmIs the shear modulus of the rock skeleton,
is porosity, p is the ratio of the first fluid and the second fluid saturation, p1Is a fluid-containing one degree of saturation, p2And the saturation degree of the fluid II is η, the viscosity coefficient of the fluid is η, kappa is the permeability, k is the complex wave number of the longitudinal wave, d is the thickness of the medium, i is an imaginary number unit, and omega is the angular frequency, wherein the density of the fluid I is lower than that of the fluid II, and deltar represents the change of the internal stress of the rock.
B. Calculating longitudinal wave velocity, transverse wave velocity and density of saturated water, saturated oil and saturated gas by using a sandstone White model based on the physical property parameters of the rock matrix and the elastic modulus of a fluid saturated medium; the calculation formula is as follows:
wherein the density of the medium of the saturated fluid I (i.e. the upper medium) is rho1The density of the medium of the saturated fluid two (i.e., the lower medium) is ρ2The saturation of the fluid containing one (i.e. the upper fluid) is p1Containing a fluid two (i.e. containing a lower layer)Fluid) saturation of p2Sandstone longitudinal wave velocity (i.e. the velocity of the longitudinal wave) is vpThe sandstone transverse wave velocity (namely the transverse wave velocity) is vsThe density of the tri-sandstone (i.e. the density) is ρd(ii) a Wherein the density of the first saturated fluid is lower than the density of the second saturated fluid.
The sandstone hydrocarbon-bearing reservoir prediction factor construction unit is used for constructing sandstone hydrocarbon-bearing reservoir prediction factors, wherein the expressions of the sandstone hydrocarbon-bearing reservoir prediction factors comprise longitudinal wave velocity, transverse wave velocity and density, and the sandstone hydrocarbon-bearing reservoir prediction factors are respectively transmitted to the hydrocarbon-bearing reservoir prediction threshold analysis unit and the sandstone hydrocarbon-bearing reservoir prediction unit; the expression of the constructed sandstone hydrocarbon-bearing reservoir prediction factor F is as follows:
wherein F is sandstone hydrocarbon-bearing reservoir prediction factor vpIs sandstone longitudinal wave velocity, vsIs the sandstone shear wave velocity, rhodIs the density of the sandstone and the sand is,
is porosity.
A hydrocarbon-bearing reservoir prediction threshold value analysis unit which is connected with the velocity density calculation unit and the sandstone hydrocarbon-bearing reservoir prediction factor construction unit and is used for calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors based on the longitudinal wave velocity, the transverse wave velocity and the density of the saturated water, the saturated oil and the saturated gas which are calculated by the velocity density calculation unit and the sandstone hydrocarbon-bearing reservoir prediction factors constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit, determining the sandstone hydrocarbon-bearing reservoir prediction threshold value (specifically, the longitudinal wave velocity, the transverse wave velocity and the density of the saturated water, the saturated oil and the saturated gas which are calculated are substituted into a sandstone hydrocarbon-bearing reservoir prediction factor formula to respectively obtain the distribution characteristics of the saturated water, the saturated oil and the prediction factors of the saturated gas, and determining the sandstone hydrocarbon-bearing reservoir prediction threshold value by analyzing the distribution characteristics of the prediction factors of different saturated fluids, wherein the sandstone hydrocarbon-bearing reservoir prediction threshold value can eliminate the influence of ) Transmitting the sandstone hydrocarbon-bearing reservoir prediction threshold value to a sandstone hydrocarbon-bearing reservoir prediction unit;
the sandstone hydrocarbon-bearing reservoir prediction unit is connected with the data acquisition unit, the sandstone hydrocarbon-bearing reservoir prediction factor construction unit and the hydrocarbon-bearing reservoir prediction threshold analysis unit, and is used for calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data acquired by the data acquisition unit and the sandstone hydrocarbon-bearing reservoir prediction factor constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold determined by the hydrocarbon-bearing reservoir prediction threshold analysis unit; specifically, the acquired logging curve data is substituted into a sandstone hydrocarbon-bearing reservoir prediction factor formula to obtain a hydrocarbon-bearing reservoir prediction factor curve, and then judgment is carried out according to a hydrocarbon-bearing reservoir prediction threshold value: and the curve part of the hydrocarbon-bearing reservoir prediction factor which is greater than or equal to the threshold value is a hydrocarbon-bearing reservoir, and the curve part which is smaller than the threshold value is an aquifer or a compact layer, so that the identification of the sandstone hydrocarbon-bearing reservoir is realized.
The processes described in the claims and in the description section may include more or fewer operations, which may be performed sequentially or in parallel (e.g., using parallel processors or a multi-threaded environment).
Claims (11)
1. A log interpretation method for predicting a sandstone hydrocarbon-bearing reservoir, wherein the method comprises:
1) obtaining physical property parameters of a rock matrix and logging curve data;
2) calculating longitudinal wave velocity, transverse wave velocity and density of the sandstone reservoir saturated with different fluids based on the physical parameters of the rock matrix obtained in the step 1);
3) constructing a sandstone hydrocarbon-bearing reservoir prediction factor, wherein the expression of the sandstone hydrocarbon-bearing reservoir prediction factor comprises longitudinal wave velocity, transverse wave velocity and density;
4) calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir which are obtained by calculation in the step 2) when the sandstone reservoir is saturated with different fluids, and determining the sandstone hydrocarbon-bearing reservoir prediction threshold;
5) and (3) predicting the sandstone hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold value determined in the step 4) by utilizing the logging curve data obtained in the step 1) and the sandstone hydrocarbon-bearing reservoir prediction factor curve calculated by the sandstone hydrocarbon-bearing reservoir prediction factor constructed in the step 3).
2. The method of claim 1, wherein the rock matrix property parameter comprises: rock matrix bulk modulus, rock skeleton bulk modulus, shear modulus of rock skeleton, density, porosity and mixed fluid bulk modulus, fluid viscosity coefficient, permeability, medium thickness.
3. The method of claim 1, wherein the well log data comprises a compressional velocity profile, a shear velocity profile, a density profile, and a neutron porosity profile.
4. The method according to claim 1, wherein the step 2) of calculating by using a sandstone White model specifically comprises the following steps:
A. calculating the elastic modulus of the fluid saturated medium by using a sandstone White model based on the physical property parameters of the rock matrix;
B. and calculating the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when different fluids are saturated by utilizing the sandstone White model based on the physical property parameters of the rock matrix and the elastic modulus of the fluid saturated medium.
5. The method of claim 4, wherein the equation for calculating the modulus of elasticity of the fluid saturated medium is:
wherein the content of the first and second substances,
wherein E is the modulus of elasticity of the fluid saturated medium, E0Is the modulus of elasticity, K, of dry rockmIs the bulk modulus of the rock skeleton, KgIs the bulk modulus of the rock matrix, KfFor mixed fluid bulk modulus, μmIs the shear modulus of the rock skeleton,
is porosity, p is the ratio of the first fluid and the second fluid saturation, p1Is a fluid-containing one degree of saturation, p2The saturation degree of the fluid II is η, the viscosity coefficient of the fluid is η, k is the permeability, k is the complex wave number of the longitudinal wave, d is the thickness of the medium, i is an imaginary number unit, omega is an angular frequency, the density of the fluid I is lower than that of the fluid II, and delta r is the change of the internal stress of the rock.
6. The method of claim 4, wherein the formula for calculating compressional velocity, shear velocity and density is:
wherein the density of the medium of the saturated fluid I is rho1The density of the medium of the saturated fluid two is rho2Containing a fluid with a degree of saturation p1The secondary saturation of the fluid is p2Longitudinal wave velocity vpThe transverse wave velocity is vsDensity is rhod(ii) a Wherein the density of the first fluid is lower than the density of the second fluid.
7. The method of claim 1, wherein in step 3), the sandstone hydrocarbon-bearing reservoir predictor has the expression:
wherein F is sandstone hydrocarbon-bearing reservoir prediction factor vpIs the velocity of the longitudinal wave, vsIs the transverse wave velocity, pdIn order to be the density of the mixture,
is porosity.
8. The method of claim 1, wherein in the step 4), the sandstone hydrocarbon-bearing reservoir prediction factor distribution characteristics of the sandstone reservoir when the sandstone reservoir is saturated with different fluids are analyzed, the sandstone hydrocarbon-bearing reservoir prediction threshold value is determined, and the sandstone hydrocarbon-bearing reservoir prediction threshold value is determined by respectively carrying out rock physical template and sensitivity analysis on the sandstone reservoir prediction factors when the sandstone reservoir is saturated with different fluids.
9. The method of claim 1, wherein the saturated different fluids comprise saturated water, saturated oil, and saturated gas.
10. The method of claim 1, wherein in step 5), the performing hydrocarbon-bearing reservoir prediction according to the sandstone hydrocarbon-bearing reservoir prediction threshold determined in step 4) by using the logging curve data obtained in step 1) and the sandstone hydrocarbon-bearing reservoir predictor curve calculated by the sandstone hydrocarbon-bearing reservoir predictor constructed in step 3) comprises: substituting the acquired logging curve data into a sandstone hydrocarbon-bearing reservoir prediction factor formula to obtain a hydrocarbon-bearing reservoir prediction factor curve, and then judging according to a hydrocarbon-bearing reservoir prediction threshold value: and the curve part of the hydrocarbon-bearing reservoir prediction factor which is greater than or equal to the threshold value is a hydrocarbon-bearing reservoir, and the curve part which is smaller than the threshold value is an aquifer or a compact layer, so that the identification of the sandstone hydrocarbon-bearing reservoir is realized.
11. An apparatus for predicting a sandstone hydrocarbon-bearing reservoir, wherein the apparatus is used for implementing the well logging interpretation method for predicting a sandstone hydrocarbon-bearing reservoir of any one of claims 1-10, and the apparatus comprises:
the data acquisition unit is used for acquiring physical property parameters of the rock matrix and logging curve data;
the velocity density calculation unit is used for calculating the longitudinal wave velocity, the transverse wave velocity and the density of the sandstone reservoir when different fluids are saturated on the basis of the physical parameters of the rock matrix acquired by the data acquisition unit;
the sandstone hydrocarbon-bearing reservoir prediction factor construction unit is used for constructing sandstone hydrocarbon-bearing reservoir prediction factors, wherein the expressions of the sandstone hydrocarbon-bearing reservoir prediction factors comprise longitudinal wave velocity, transverse wave velocity and density;
the hydrocarbon-bearing reservoir prediction threshold analysis unit is used for calculating and analyzing the distribution characteristics of the sandstone hydrocarbon-bearing reservoir prediction factors when the sandstone reservoir is saturated with different fluids based on the compressional wave velocity, the shear wave velocity and the density of the sandstone reservoir when the sandstone reservoir is saturated with different fluids, which are calculated by the velocity density calculation unit, and the sandstone hydrocarbon-bearing reservoir prediction factors constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit, and determining the sandstone hydrocarbon-bearing reservoir prediction threshold;
and the sandstone hydrocarbon-bearing reservoir prediction unit is used for calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by using the logging curve data acquired by the data acquisition unit and the sandstone hydrocarbon-bearing reservoir prediction factor constructed by the sandstone hydrocarbon-bearing reservoir prediction factor construction unit and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold determined by the hydrocarbon-bearing reservoir prediction threshold analysis unit.
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