CN111458747A - Method and device for predicting coal bed gas by four parameters - Google Patents
Method and device for predicting coal bed gas by four parameters Download PDFInfo
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Abstract
The invention discloses a method and a device for predicting coal bed gas by four parameters, and relates to the technical field of coal bed gas exploration and development. The method comprises the following steps: simplifying the Zoeppritz equation set to obtain an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
is a relative change factor of the bulk modulus,
Is a relative change factor of Lame constant,
Is a shearRelative change factor of shear modulus,
Is density relative change factor; under the constraint condition of logging, performing simultaneous inversion on the pre-stack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a pre-stack maximum likelihood statistical method; and predicting the coal bed gas according to the inversion result.
Description
Technical Field
The invention relates to the technical field of coal bed gas exploration and development, in particular to a method and a device for predicting coal bed gas by four parameters.
Background
The coal bed gas refers to gas in a coal bed, the main component of the gas is methane, and more than 95% of the coal bed gas exists in the coal bed in an adsorption state under the condition of an underground warm-pressing reservoir. On one hand, the coal bed gas is the cause of gas outburst and explosion in coal mining, on the other hand, the coal bed gas is also a clean energy source, and if the coal bed gas can be well developed and utilized, the energy crisis can be relieved to a certain extent, and the human society is benefited.
The gas adsorption capacity of the coal seam is influenced by various factors, such as coal seam heterogeneity, stratum temperature and pressure, underground water flow, geological structure movement and the like, and the coal seam gas exploration and development difficulty is large due to large difference of the adsorption capacity. Currently, the exploration and development of coal bed gas mainly depend on geological research results, seismic routine processing explanation and drilling and logging results. Geological research results only can provide guidance directions for coal bed methane exploration and development and are difficult to be used as accurate bases for actual exploration and development; the reliability of drilling and logging data is high, but the implementation cost is high, and the coal bed condition at a well point can be only obtained, so that the transverse macroscopic deployment of coal bed gas exploration and development is not facilitated. Although the seismic routine processing explanation can provide the spatial morphology, fracture spread, thickness distribution and the like of the coal bed, the local enrichment part of the coal bed gas is difficult to detect. Therefore, the coal bed gas exploration development industry needs a new technology for predicting a high-yield area with local coal bed gas enrichment urgently, so that the coal bed gas exploration success rate is improved, and the proportion of high-yield development wells is increased.
Statistical analysis shows that negative correlation exists between the gas content of the coal bed and elastic parameters such as the density, the longitudinal wave velocity, the transverse wave velocity and the like of a reservoir, and the negative correlation can form the rock physical basis of the AVO (amplitude coverage offset) technology of the coal bed gas. Experiments have shown that coalbed methane reservoir AVO anomalies are typical class IV AVO anomalies, with intercept opposite in sign to gradient and amplitude always decreasing with increasing offset. The strong reflection amplitude and the high signal-to-noise ratio of the coal bed gas reservoir and the relatively stable structural characteristics enable the gas content of the coal bed and the AVO abnormal characteristics to form a corresponding relation, and the method becomes the basis for predicting the enrichment of the coal bed gas. The defects in the United states are that the change of the coal bed elasticity parameters caused by the 'gas-rich' coal bed is very small, the interference factors are more, and meanwhile, the AVO prediction technology of the coal bed gas has the possibility of having multi-solution and is difficult to quantify. Therefore, the AVO technology developed for coal bed gas exploration needs to be innovative from theory to method, and needs to be a new method suitable for coal bed gas detection.
Disclosure of Invention
The invention aims to provide a method and a device for predicting coal bed gas by four parameters, aiming at the problems.
The embodiment of the invention provides a method for predicting coal bed gas by four parameters, which comprises the following steps:
simplifying the Zoeppritz equation set to obtain an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
under the constraint condition of logging, performing simultaneous inversion on the pre-stack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a pre-stack maximum likelihood statistical method;
and predicting the coal bed gas according to the inversion result.
Preferably, the predicting the coal seam according to the inversion result specifically includes:
and obtaining an inversion attribute abnormal area by using the inverted volume modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor, and predicting the coal bed gas enrichment area and the coal bed crack development area by synthesizing actual exploration information.
Preferably, the performing the simultaneous inversion of the bulk modulus relative change factor, the lamel constant relative change factor, the shear modulus relative change factor and the density relative change factor before the stacking specifically includes:
converting the common-midpoint seismic gather into a common-reflection-point offset seismic gather;
under the control of the root mean square speed of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
performing horizon interpretation on the superposed profile, converting logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on longitudinal wave, transverse wave and density logging data, and establishing a three-dimensional spatial velocity model;
carrying out parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and under the condition of logging statistical constraint, performing simultaneous inversion on the prestack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a prestack maximum likelihood statistical method.
Preferably, the acquiring an inversion attribute abnormal region by using the inverted relative change factor of the bulk modulus, the relative change factor of the lame constant, the relative change factor of the shear modulus and the relative change factor of the density, and predicting the coal bed methane enrichment region and the coal bed fracture development region by synthesizing actual exploration information specifically includes:
drawing a four-parameter profile, a plan, an bedding view and a stereo according to the inversion body of the four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
analyzing the four-parameter profile, plan, bedding and stereogram to obtain a four-parameter inversion attribute abnormal area;
and combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
Preferably, the common reflection point offset seismic gather is a multiple-covered common reflection point offset seismic gather containing only primary reflected wave energy.
The embodiment of the invention also provides a device for predicting the coal bed gas by four parameters, which comprises the following steps:
the acquisition unit is used for simplifying the Zoeppritz equation set to acquire an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
the inversion unit is used for simultaneously inverting the pre-stack relative change factor of the volume modulus, the pre-stack relative change factor of the Lame constant, the pre-stack relative change factor of the shear modulus and the pre-stack relative change factor of the density by using a pre-stack maximum likelihood statistical method under the well logging constraint condition;
and the prediction unit is used for predicting the coal bed gas according to the inversion result.
Preferably, the prediction unit is specifically configured to:
and obtaining an inversion attribute abnormal area by using the inverted volume modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor, and predicting the coal bed gas enrichment area and the coal bed crack development area by synthesizing actual exploration information.
Preferably, the inversion unit is specifically configured to:
converting the common-midpoint seismic gather into a common-reflection-point offset seismic gather;
under the control of the root mean square speed of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
performing horizon interpretation on the superposed profile, converting logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on longitudinal wave, transverse wave and density logging data, and establishing a three-dimensional spatial velocity model;
carrying out parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and under the condition of logging statistical constraint, performing simultaneous inversion on the prestack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a prestack maximum likelihood statistical method.
Preferably, the prediction unit is specifically configured to:
drawing a four-parameter profile, a plan, an bedding view and a stereo according to the inversion body of the four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
analyzing the four-parameter profile, plan, bedding and stereogram to obtain a four-parameter inversion attribute abnormal area;
and combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
Preferably, the common reflection point offset seismic gather is a multiple-covered common reflection point offset seismic gather containing only primary reflected wave energy.
The embodiment of the invention provides a method and a device for predicting coal bed gas by four parameters, wherein the method comprises the following steps: simplifying the Zoeppritz equation set to obtain an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for predicting coal bed methane with four parameters according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the relationship between gas content and density according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a relationship between gas content and longitudinal wave velocity provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a relationship between gas content and shear wave velocity according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a three-layer geological theoretical model of a coalbed methane reservoir provided by an embodiment of the invention;
FIG. 6 is a schematic cross-sectional view of a seismic forward modeling system according to an embodiment of the present invention;
fig. 7 is a schematic diagram illustrating that the absolute value of the relative variation of four parameters of the reflection interface of the coal seam roof increases with the gas content of the coal seam;
fig. 8 is a schematic diagram that an absolute value of three-parameter relative variation of a coal seam floor reflection interface provided in an embodiment of the present invention increases with an increase in gas content of a coal seam.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart illustrating a four-parameter method for predicting coal bed methane according to an embodiment of the present invention, where the method may be applied to at least coal bed methane detection.
As shown in fig. 1, the method mainly comprises the following steps:
wherein the content of the first and second substances,
102, under the condition of logging constraint, simultaneously inverting the pre-stack relative change factor of the volume modulus, the pre-stack relative change factor of the Lame constant, the pre-stack relative change factor of the shear modulus and the pre-stack relative change factor of the density by using a pre-stack maximum likelihood statistical method;
and 103, predicting the coal bed gas according to the inversion result.
Before the method for predicting coal bed gas by four parameters provided by the embodiment of the invention is introduced, the derivation of an elastic modulus method approximate expression of a Zeoppritz equation set is introduced:
in practical applications, the velocity of the rock is determined by the elastic modulus and the density of the rock, and the shear wave velocity Vs and the longitudinal wave velocity Vp can be expressed by the density and the elastic modulus, as shown in formula (1) and formula (2):
the Zoeppritz equation set expresses the relationship between the reflection and transmission coefficients of various wave modes when a plane longitudinal wave is incident on an infinite horizontal reflection interface and the longitudinal wave velocity, the transverse wave velocity, the density and the incidence angle of rocks on two sides of the reflection interface. However, in practical applications, the exact complete set of Zoeppritz equations is too complex and the information needed to solve the set of equations is generally unknown. Therefore, various researchers have proposed various approximations of the Zoeppritz system of equations under different assumptions for different research purposes. Aki and Richards are widely cited (see Aki, K.I. and Richards, P.G., 1980, "quantitative Seismoggy", W.H. Freeman Co., P.153). Assuming that the relative change of the elastic characteristics of the media on both sides of the reflecting interface is relatively small, the longitudinal wave reflection coefficient R (θ) can be expressed by the following formula (3):
wherein the content of the first and second substances,
in practical application, Vp1、Vs1、ρ1Respectively the longitudinal wave velocity, the transverse wave velocity and the density of the medium coated on the interface；Vp2、Vs2、ρ2The longitudinal wave velocity, the transverse wave velocity and the density of the interface underlying medium respectively; vp、VsRho is the average speed of longitudinal wave, the average speed of transverse wave and the average density of the medium at two sides of the interface respectively; theta1,θ2Respectively, the incident angle and the refraction angle of the longitudinal wave, and theta is the average value of the incident angle and the refraction angle.
Since the velocity of seismic waves propagating in subsurface rock is determined by the modulus of elasticity and the density of the rock, the velocity in equation (3) can be replaced by the modulus of elasticity and the density. Let lambda1，μ1，k1And ρ1Denotes the modulus of elasticity of the overlying medium, let λ2，μ2，k2And ρ2Expressing the elastic modulus of the underlying medium, let λ, μ, k, ρ be expressed by the following equation (4), equation (5), equation (6) and equation (7), respectively:
since it has been assumed that the relative change in the elastic characteristics of the media across the reflective interface is relatively small, equations (1) and (2) hold approximately, with a small percentage error from the actual average. Differentiating (1) and (2) yields the following equation:
substituting equation (7), equation (8) and equation (9) into equation (3), after finishing the simplification, equation (3) may become:
wherein the content of the first and second substances,
from this point forward, equation (10) is referred to as the Zeoppritz equation set elastic modulus method approximation; the three terms at the right end of the formula (10) are respectively called a volume modulus term, a Lame constant term, a shear modulus term and a density term from left to right; will be provided with
Referred to as the relative change in bulk modulus, the relative change in lame constant, the relative change in shear modulus, and the relative change in density, respectively.
Wherein the content of the first and second substances,
is not the Lame constant λ or the shear modulus μ or the bulk modulus, but is (λ +2 μ) or
In a strict sense of speaking,
it is considered that the relative change of lame constant, the relative change of shear modulus, and the change of bulk modulus are not the same, but
The nature of the molecule
Referred to as relative change in lame constant, relative change in shear modulus, and change in bulk modulus.
Further, comparing the coefficients of the terms on the right end of equation (3) and equation (10), the obvious difference is: the coefficient of the first term and the second term of the formula (3) has the ratio of longitudinal wave speed and transverse wave speed, namely
While the coefficients of the right-hand terms of equation (10) are only a function of theta. Due to the fact that
Is unknown, if the inversion is done using equation (3), it needs to be assumed
Which will lead to unpredictable errors. Therefore, equation (3) cannot be used for inversion
Around 2003, China has raised a hot tide using equation (3) for three-parameter inversion, and finally, the heat tide is no longer rapid, because of this. Formula (II)(10) The coefficients of the right-hand terms are only a function of theta, if the inversion is done using equation (10)
The value of (A) need not be assumed
The value of which reduces errors from the source. Theta is the average of the angle of incidence and angle of refraction, and there are well established calculation methods.
Comparing the elastic parameters used in the formula (3) and the formula (10), wherein the longitudinal wave velocity Vp used in the formula (3) is a function of the Lame constant lambda, the shear modulus mu and the density rho, and is a quite complex elastic parameter; shear wave velocity Vs is a function of shear modulus μ and density ρ, and is also a complex parameter, so even if the inversion is obtained
Their multi-resolution will also limit their value. The elasticity parameters λ, μ, ρ and k used in the formula (10) are the most basic elasticity parameters, and the relationship between the relative variation and the gas content of the coal bed is conveniently searched.
In step 101, the Zoeppritz equation set is simplified to obtain equation (10):
in the formula (9), the reaction mixture,
In practical applications, step 102 mainly includes the following steps:
step 1021, converting the common-center seismic gather into a common reflection point offset seismic gather;
step 1022, under the control of root mean square velocity of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
1023, performing horizon interpretation on the superposed section, converting the logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on the logging data of longitudinal waves, transverse waves and density, and establishing a three-dimensional spatial velocity model;
step 1024, performing parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and 1025, simultaneously inverting the pre-stack relative change factor of the volume modulus, the relative change factor of the Lame constant, the relative change factor of the shear modulus and the relative change factor of the density by using a pre-stack maximum likelihood statistical method under the constraint condition of logging statistics.
In step 1022, the common reflection point offset seismic gather is a multiply-covered common reflection point offset seismic gather that includes only primary reflected wave energy.
In practical application, step 103 may be to obtain an inversion attribute abnormal region by using the inverted relative change factor of the bulk modulus, the relative change factor of the lame constant, the relative change factor of the shear modulus, and the relative change factor of the density, and predict the coalbed methane enrichment region and the coalbed fracture development region by synthesizing actual exploration information.
Further, acquiring an inversion attribute abnormal area by using the inverted relative change factor of the bulk modulus, the relative change factor of the lame constant, the relative change factor of the shear modulus and the relative change factor of the density, and predicting a coal bed gas enrichment area and a coal bed crack development area by synthesizing actual exploration information, wherein the method mainly comprises the following steps:
step 1031, drawing a four-parameter profile, a plan view, an in-layer view and a stereo view according to the inversion body with four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
step 1032, analyzing the four-parameter section view, the plan view, the bedding view and the stereo view to obtain a four-parameter inversion attribute abnormal area;
and 1033, combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
The geological meaning of the coal bed with the elastic modulus approximate formula of four-parameter relative variation is further described as follows:
in order to illustrate the method for detecting the coal bed gas enrichment area by the four-parameter relative variation provided by the embodiment of the invention, some rock physical research results need to be introduced.
According to the gas content and density of the coal bed gas reservoir and the longitudinal wave speed and the transverse wave speed of the coal bed gas reservoir obtained by well logging, the research finds that the gas content of the coal bed gas reservoir and the density, the longitudinal wave speed and the transverse wave speed have a negative correlation relationship, namely the gas content is high, the density is low, the longitudinal wave speed is low, the transverse wave speed is low, the gas content is low, the density is high, the longitudinal wave speed is high and the transverse wave speed is high.
Fig. 2 is a schematic diagram of a relationship between gas content and density according to an embodiment of the present invention, fig. 3 is a schematic diagram of a relationship between gas content and longitudinal wave velocity according to an embodiment of the present invention, and fig. 4 is a schematic diagram of a relationship between gas content and transverse wave velocity according to an embodiment of the present invention; as shown in fig. 2, fig. 3 and fig. 4, the relationship between the gas content of the coalbed methane reservoir and the density, compressional wave velocity and shear wave velocity thereof can be fitted according to the above linear relationship, which is specifically shown in the following formula:
Vg＝-25.491*D+47.871，R＝0.791 (16)
Vg＝-0.0062*Vp+27.41，R＝0.783 (17)
Vg＝-0.0115*Vs+28.172，R＝0.803 (18)
in the above formula VgIs the gas content, in m3Per ton; d is the density in g/cm3；VpIs the wave velocity in m/s; vsIs the transverse wave velocity in m/s.
The number of sampling points used in fitting the formula (16), the formula (17) and the formula (18) is limited, and parameters obtained by conversion from these relations cannot replace data measured in a laboratory, but these relations and the trends of the correlation between the gas content and the elasticity parameter shown in fig. 2, 3 and 4 are reliable.
According to the formula (16), the formula (17), and the formula (18), the following relationships can be obtained by conversion, respectively:
D＝1.877957-0.03923*Vg (19)
Vp＝4420.968-161.29*Vg (20)
Vs＝2449.739-86.9565*Vg (21)
suppose VgThe value of which is from 20m3Change of/t to 0m3T, predicted from the above three equations and VgThe density, longitudinal wave velocity, and transverse wave velocity corresponding to the values are shown in table 1:
table 1: according to the assumed VgAnd the elastic parameters of the coal bed gas reservoir predicted by the formula (19), the formula (20) and the formula (21)
| Hypothetical Vg | Predicted density | Predicted longitudinal wave velocity | Predicted |
| 20 | 1.093 | 1195.161 | 710.609 |
| 15 | 1.290 | 2001.613 | 1145.391 |
| 10 | 1.486 | 2808.065 | 1580.174 |
| 5 | 1.682 | 3614.516 | 2014.957 |
| 0 | 1.878 | 4420.968 | 2449.739 |
And (3) obtaining the density, the longitudinal wave velocity and the transverse wave velocity of surrounding rocks of the coal bed gas reservoir and the density, the longitudinal wave velocity and the transverse wave velocity of the coal bed gas reservoir predicted in the table 1 by using statistical research, and constructing a three-layer geological model shown in the figure 5. According to the geological model shown in fig. 5, the thickness of the coal seam is equal to 1/4 wavelengths, the top interface of the coal seam is in a negative phase, and the bottom interface of the coal seam is in a positive phase. The forward modeling analysis performed results in the seismic forward modeling profile schematic depicted in fig. 6.
Modifying the parameters of the coal bed gas reservoir to the elastic parameters predicted by the table 1, and substituting the parameters of the geological model into the formula
Can obtain a different VgThe values of which correspond to the relative change in density, the relative change in shear modulus, the relative change in lame constant, and the relative change in bulk modulus are shown in table 2 and fig. 7 and 8. The data result proves that when the gas content of the coal bed gas reservoir is increased, the absolute values of the relative variation of the density, the relative variation of the shear modulus, the relative variation of the Lame constant and the relative variation of the bulk modulus of the coal bed roof and the coal bed floor are increased.
TABLE 2 statistical calculation of geomodel parameters
The research shows that the lithology of the surrounding rock of the coal bed top and bottom plate is not changed, the gas content of the coal bed gas reservoir is large, and the density relative variation of the reflecting interface of the reservoir top plate and the reflecting interface of the bottom plate is changed
Is large. Therefore, relative change in density
The inversion is an indicator factor for predicting the gas content of the coal bed gas reservoir, and the gas content of the coal bed gas reservoir can be predicted according to the abnormal strength, so that the enriched part of the coal bed gas is predicted.
Shear modulus, also known as the stiffness of an elastomer, represents the ability of an elastomer to resist shear deformation. The main factors influencing the size of the rock shear modulus comprise mineral components, compaction degree, cementing strength, porosity, fracture development degree and the like.If the mineral composition, compaction and bond strength of the rock are not very variable, then the extent of fracture development is a determining factor in the shear modulus of the rock. Therefore, the relative change of the shear modulus of the media on two sides of the reflecting interface of the top plate and the bottom plate of the coal seam is obtained through inversion by a four-parameter elastic modulus method
And indicating the development degree of the coal reservoir fracture and predicting a high permeability area of the coal bed methane reservoir.
Relative change of Lame constant
In conventional oil and gas detection, free natural gas can be detected, but coal bed gas is mainly adsorbed natural gas. The significance of the relative change of the Lame constant in the coalbed methane reservoir is not clear at present and needs to be further explored.
The bulk modulus k represents the ratio of pressure to deformation of the medium, and the change of the bulk modulus
Can be used as a sensitive parameter for porosity change because the bulk modulus is related to the degree of compression of the media, and is large if the media compression space is small, and small if the media is easily compressed.
Based on the same inventive concept, the embodiment of the invention provides a device for predicting coal bed gas by four parameters, and as the principle of solving the technical problem of the device is similar to that of a method for predicting coal bed gas by four parameters, the implementation of the device can refer to the implementation of the method, and repeated parts are not repeated.
The device for predicting the coal bed gas by four parameters provided by the embodiment of the invention comprises an acquisition unit, an inversion unit and a prediction unit.
The acquisition unit is used for simplifying the Zoeppritz equation set to acquire an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
the inversion unit is used for simultaneously inverting the pre-stack relative change factor of the volume modulus, the pre-stack relative change factor of the Lame constant, the pre-stack relative change factor of the shear modulus and the pre-stack relative change factor of the density by using a pre-stack maximum likelihood statistical method under the well logging constraint condition;
and the prediction unit is used for predicting the coal bed gas according to the inversion result.
Preferably, the prediction unit is specifically configured to:
and obtaining an inversion attribute abnormal area by using the inverted volume modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor, and predicting the coal bed gas enrichment area and the coal bed crack development area by synthesizing actual exploration information.
Preferably, the inversion unit is specifically configured to:
converting the common-midpoint seismic gather into a common-reflection-point offset seismic gather;
under the control of the root mean square speed of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
performing horizon interpretation on the superposed profile, converting logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on longitudinal wave, transverse wave and density logging data, and establishing a three-dimensional spatial velocity model;
carrying out parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and under the condition of logging statistical constraint, performing simultaneous inversion on the prestack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a prestack maximum likelihood statistical method.
Preferably, the prediction unit is specifically configured to:
drawing a four-parameter profile, a plan, an bedding view and a stereo according to the inversion body of the four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
analyzing the four-parameter profile, plan, bedding and stereogram to obtain a four-parameter inversion attribute abnormal area;
and combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
Preferably, the common reflection point offset seismic gather is a multiple-covered common reflection point offset seismic gather containing only primary reflected wave energy.
It should be understood that the above four-parameter coalbed methane predicting device includes only the units that are logically divided according to the functions implemented by the equipment device, and in practical application, the above units may be stacked or separated. The functions of the four-parameter coalbed methane prediction device provided by this embodiment are in one-to-one correspondence with the four-parameter coalbed methane prediction method provided by the above embodiment, and for a more detailed processing flow implemented by the device, detailed description is already given in the first method embodiment, and detailed description is not given here.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A four-parameter method for predicting coal bed gas is characterized by comprising the following steps:
simplifying the Zoeppritz equation set to obtain an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
is a relative change factor of the bulk modulus,
Is a relative change factor of Lame constant,
Is a relative change factor of the shear modulus,
Is density relative change factor;
under the constraint condition of logging, performing simultaneous inversion on the pre-stack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a pre-stack maximum likelihood statistical method;
and predicting the coal bed gas according to the inversion result.
2. The method of claim 1, wherein the predicting the coal seam according to the inversion result specifically comprises:
and obtaining an inversion attribute abnormal area by using the inverted volume modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor, and predicting the coal bed gas enrichment area and the coal bed crack development area by synthesizing actual exploration information.
3. The method according to claim 1 or 2, wherein said performing simultaneous inversion of the bulk modulus relative change factor, the lame constant relative change factor, the shear modulus relative change factor and the density relative change factor before stacking specifically comprises:
converting the common-midpoint seismic gather into a common-reflection-point offset seismic gather;
under the control of the root mean square speed of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
performing horizon interpretation on the superposed profile, converting logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on longitudinal wave, transverse wave and density logging data, and establishing a three-dimensional spatial velocity model;
carrying out parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and under the condition of logging statistical constraint, performing simultaneous inversion on the prestack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a prestack maximum likelihood statistical method.
4. The method of claim 2, wherein the obtaining of inversion attribute abnormal regions by using the inverted relative change factor of bulk modulus, the relative change factor of lame constant, the relative change factor of shear modulus and the relative change factor of density and the predicting of coalbed methane enrichment regions and coalbed fracture development regions by integrating actual exploration information specifically comprises:
drawing a four-parameter profile, a plan, an bedding view and a stereo according to the inversion body of the four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
analyzing the four-parameter profile, plan, bedding and stereogram to obtain a four-parameter inversion attribute abnormal area;
and combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
5. The method of claim 3, wherein the common reflection point offset seismic gather is a multiply-covered common reflection point offset seismic gather containing only primary reflected wave energy.
6. A four parameter coalbed methane predicting apparatus, comprising:
the acquisition unit is used for simplifying the Zoeppritz equation set to acquire an elastic modulus approximate expression of the Zoeppritz equation set; wherein the elastic modulus approximation formula of the Zoeppritz equation system is as follows:
wherein the content of the first and second substances,
is a relative change factor of the bulk modulus,
Is a relative change factor of Lame constant,
Is a relative change factor of the shear modulus,
Is density relative change factor;
the inversion unit is used for simultaneously inverting the pre-stack relative change factor of the volume modulus, the pre-stack relative change factor of the Lame constant, the pre-stack relative change factor of the shear modulus and the pre-stack relative change factor of the density by using a pre-stack maximum likelihood statistical method under the well logging constraint condition;
and the prediction unit is used for predicting the coal bed gas according to the inversion result.
7. The apparatus as recited in claim 6, wherein said prediction unit is specifically configured to:
and obtaining an inversion attribute abnormal area by using the inverted volume modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor, and predicting the coal bed gas enrichment area and the coal bed crack development area by synthesizing actual exploration information.
8. The apparatus of claim 6 or 7, wherein the inversion unit is specifically configured to:
converting the common-midpoint seismic gather into a common-reflection-point offset seismic gather;
under the control of the root mean square speed of seismic data processing, converting the common reflection point offset distance seismic gather into a common reflection point angle gather file;
performing horizon interpretation on the superposed profile, converting logging data of a depth domain into data of a time domain by using horizon control, performing three-dimensional spatial interpolation on longitudinal wave, transverse wave and density logging data, and establishing a three-dimensional spatial velocity model;
carrying out parameter statistical analysis on the target interval, and establishing logging constraint conditions of inversion parameters;
and under the condition of logging statistical constraint, performing simultaneous inversion on the prestack bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor by using a prestack maximum likelihood statistical method.
9. The apparatus as recited in claim 7, wherein said prediction unit is specifically configured to:
drawing a four-parameter profile, a plan, an bedding view and a stereo according to the inversion body of the four parameters of the bulk modulus relative change factor, the Lame constant relative change factor, the shear modulus relative change factor and the density relative change factor;
analyzing the four-parameter profile, plan, bedding and stereogram to obtain a four-parameter inversion attribute abnormal area;
and combining the four-parameter inversion attribute abnormal area with actual exploration and development information to predict a coal bed gas enrichment area.
10. The apparatus of claim 8, wherein the common reflection point offset seismic gather is a multiply-covered common reflection point offset seismic gather containing only primary reflected wave energy.
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