SEISMIC ROCK PHYSICS INVERSION METHOD BASED ON LARGE AREA TIGHT RESERVOIR

0Associated
Cases 
0Associated
Defendants 
0Accused
Products 
0Forward
Citations 
0
Petitions 
1
Assignment
First Claim
1. A seismic rock physics inversion method based on a large area tight reservoir, wherein comprising the following specific steps:
 step 101;
predicting a wave response dispersion based on a poroelasticity theory, building a multiscale rock physics model, to associate with multiscale data, wherein the building a multiscale rock physics model is based on impact exerted by mineral constituents, a pore structure, and a formation environment of a rock on a wave response feature of the rock, and determining that reservoir environmental factors comprise a temperature and a pressure, reservoir lithological factors comprise mineral components, a pore shape, a shale content, and a pore structure, and reservoir fluid factors comprise a fluid viscosity and a gaswater patchy saturation;
step 102;
analyzing and correcting a logging interpretation result based on the model and gas testing situations of some wells, analyzing fluid sensitivity of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters which are most sensitive to a porosity and a gas saturation in a plurality of observation scales, wherein the rock physics parameters in the two scales of acoustic logging and ultrasonic wave are elastic parameters and a combination of the elastic parameters, and the elastic parameters at least comprise the following physical quantities;
a Pwave velocity Vp, a Swave velocity Vs, a Pwave impedance Zp, a Swave impedance Zs, a Pwave velocitytoSwave velocity ratio Vp/Vs, a Lamé
constant λ
, a shear modulus μ
, a product λ
ρ
of a Lamé
constant and a density, a product λ
μ
of a Lamé
constant and a shear modulus, a quasi pressure PR, a product μ
ρ
of a shear modulus and a density; and
the analyzing fluid sensitivity comprises;
measuring the Pwave velocity Vp and the Swave velocity Vs in the scale of ultrasonic wave and a wave velocity during variation of saturations of gas and water, that is, a crossplot of Vp/Vs and a wave impedance;
step 103;
preferably selecting each singlewell template to manufacture a work area standard template as a singlewell rock physics template built based on each piece of reference well data, wherein the work area standard template preferably uses a sensitivity parameter λ
ρ
as a vertical coordinate and the Pwave impedance as a horizontal coordinate; and
step 104;
finetuning, based on lateral variations and heterogeneity of reservoir geological features, input parameters of a rock physics template at coordinates of each well according to gas testing situations of all wells in a large work area, optimizing the whole work area, building a threedimensional work area rock physics template data volume, and combining the threedimensional work area rock physics template data volume with seismic prestack inversion to calculate a porosity and a saturation of a target layer;
performing largearea threedimensional rock physics template parameter inversion in the whole work area, smoothing an inversion result, and finally, outputting a reservoir parameter inversion data volume, thereby implementing quantitative interpretation on the porosity and the saturation of the reservoir; and
the building a threedimensional work area rock physics template data volume is cutting and sorting a tobeinverted and interpreted threedimensional seismic data volume according to project requirements, performing prestack threedimensional seismic inversion, and performing inverse calculation on the porosity and the saturation of the reservoir.
1 Assignment
0 Petitions
Accused Products
Abstract
A seismic rock physics inversion method based on a large area tight reservoir includes steps: building a multiscale rock physics model; analyzing fluid sensitivities of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters that are most sensitive to a porosity and a gas saturation in a plurality of observation scales; building a singlewell rock physics template, preferably a standard template; considering lateral variations and heterogeneity of reservoir geological features, finetuning input parameters of the rock physics template according to gas testing situations of all wells in a large work area, optimizing the whole work area and building a threedimensional work area rock physics template data volume, and combining the data volume with prestack seismic inversion to calculate a porosity and a saturation of a target layer; and smoothing a result and finally outputting a reservoir parameter inversion data volume.
0 Citations
No References
No References
8 Claims
 1. A seismic rock physics inversion method based on a large area tight reservoir, wherein comprising the following specific steps:
step 101;
predicting a wave response dispersion based on a poroelasticity theory, building a multiscale rock physics model, to associate with multiscale data, wherein the building a multiscale rock physics model is based on impact exerted by mineral constituents, a pore structure, and a formation environment of a rock on a wave response feature of the rock, and determining that reservoir environmental factors comprise a temperature and a pressure, reservoir lithological factors comprise mineral components, a pore shape, a shale content, and a pore structure, and reservoir fluid factors comprise a fluid viscosity and a gaswater patchy saturation;step 102;
analyzing and correcting a logging interpretation result based on the model and gas testing situations of some wells, analyzing fluid sensitivity of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters which are most sensitive to a porosity and a gas saturation in a plurality of observation scales, wherein the rock physics parameters in the two scales of acoustic logging and ultrasonic wave are elastic parameters and a combination of the elastic parameters, and the elastic parameters at least comprise the following physical quantities;
a Pwave velocity Vp, a Swave velocity Vs, a Pwave impedance Zp, a Swave impedance Zs, a Pwave velocitytoSwave velocity ratio Vp/Vs, a Lamé
constant λ
, a shear modulus μ
, a product λ
ρ
of a Lamé
constant and a density, a product λ
μ
of a Lamé
constant and a shear modulus, a quasi pressure PR, a product μ
ρ
of a shear modulus and a density; and
the analyzing fluid sensitivity comprises;
measuring the Pwave velocity Vp and the Swave velocity Vs in the scale of ultrasonic wave and a wave velocity during variation of saturations of gas and water, that is, a crossplot of Vp/Vs and a wave impedance;step 103;
preferably selecting each singlewell template to manufacture a work area standard template as a singlewell rock physics template built based on each piece of reference well data, wherein the work area standard template preferably uses a sensitivity parameter λ
ρ
as a vertical coordinate and the Pwave impedance as a horizontal coordinate; andstep 104;
finetuning, based on lateral variations and heterogeneity of reservoir geological features, input parameters of a rock physics template at coordinates of each well according to gas testing situations of all wells in a large work area, optimizing the whole work area, building a threedimensional work area rock physics template data volume, and combining the threedimensional work area rock physics template data volume with seismic prestack inversion to calculate a porosity and a saturation of a target layer;
performing largearea threedimensional rock physics template parameter inversion in the whole work area, smoothing an inversion result, and finally, outputting a reservoir parameter inversion data volume, thereby implementing quantitative interpretation on the porosity and the saturation of the reservoir; and
the building a threedimensional work area rock physics template data volume is cutting and sorting a tobeinverted and interpreted threedimensional seismic data volume according to project requirements, performing prestack threedimensional seismic inversion, and performing inverse calculation on the porosity and the saturation of the reservoir. View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
1 Specification
The present invention belongs to the field of seismic rock physics inversion technologies, and in particular, to a seismic rock physics inversion method based on a large area tight reservoir.
Currently, using seismic data to directly predict a reservoir and recognize hydrocarbon features has been developed into a research hotspot in the field of exploration geophysics, but its research difficulty is that the seismic data is a comprehensive reflection of properties of an underground reservoir in multiple aspects. Underdetermining of an inverse problem results in multiplicity in seismic interpretation and seismic prediction. Seismic rock physics, as a bridge communicating aboveground seismic data and underground reservoir parameters, is a theoretical and experimental basis of quantitative interpretation on a hydrocarboncontaining reservoir. Seismic inversion driven by rock physics helps to accurately recognize hydrocarbon features and distribution laws of an underground reservoir, so as to deal with multiplicity and limitations of a seismic inversion problem. In the study of rock physics, quantitative relationships between a rock elastic parameter and each of a reservoir physical property and a pore fluid parameter may be built to expand the conventional rock physical experimental study from a rock core scale to an oil field scale, and rock physics models in different observation scales (a rock core scale, a logging scale, and a seismic scale) are built to implement fusion between multidisciplinary data in different scales (Tang, 2008). With regard to three observation scales of seismic, logging, and ultrasonic wave experiments, currently, most geophysical scholars interpret differences among observation results in different scales by using a wave velocity dispersion mechanism induced by a pore fluid flow mechanism. Three types of pore fluid flow mechanisms are respectively: a macroscopicscale pore fluid flow mechanism (Gassmann, 1951; Biot, 1956, 1962), a grainscale pore fluid flow mechanism (Mavko, 1975; Dvorkin, 1993; Gurevich et al., 2010; Vinci et al., 2014; Papageorgiou et al., 2015), and a mesoscopicscale (larger than a pore size, but far less than a wavelength) fluid flow mechanism (White, 1975; Pride, 2003; Ba et al., 2011, 2012; Sun et al., 2015). Since a carbonatite reservoir has complex pore structures and strong lateral heterogeneity, a conventional rock physics template built based on a single pore structure and singlescale data is inapplicable to a large work area.
Chinese patent 201210335739.9 discloses “a multiscale rock physics template method and device for detecting reservoir hydrocarbon”. The method includes: obtaining a reservoir rock matrix model and a reservoir rock skeleton model, obtaining a fluidcontaining rock model according to the reservoir rock matrix model, the reservoir rock skeleton model, and fluid parameters, and obtaining a multiscale initial reservoir rock physics template according to the fluidcontaining rock model; correcting the initial reservoir rock physics template under a plurality of frequency bands according to rock physical experimental data; correcting the initial reservoir rock physics template under an acoustic logging frequency band according to a logging interpretation result; and outputting a final reservoir rock physics template after the correction, so as to carry out inversion of reservoir rock physics parameters. This method can increase precision of the rock physics template and implement the quantitative inversion of rock parameters and a saturation of a fluid. However, in this method, modeling is performed by taking a pore structure of a single type in combination with multiscale wave data into consideration, and an obvious disadvantage thereof is inapplicable to a heterogeneous reservoir whose formation pore structure type changes.
Chinese patent 201310752436.1 discloses “a gas reservoir prediction method and system of a carbonatite reservoir based on pore structure features”. The method includes: collecting a rock sample of a target layer section of the carbonatite reservoir; authenticating geological thin sheets of the rock sample so as to obtain rock basic parameters, including rock constituents, a pore shape, a surface porosity, and a sedimentary phase belt; carrying out pore permeation measurement on the rock sample so as to obtain pore permeation basic parameters including a porosity, a permeability, and a density; constructing a dry rock skeleton model according to the rock basic parameters, the pore permeation basic parameters, and a differential effective medium model; carrying out fluid substitution according to the dry rock skeleton model, so as to generate a rock physics template; obtaining prestack seismic inversion data of the carbonatite reservoir; and intersecting the prestack seismic inversion data with the rock physics template, to obtain prediction results of a porosity and a gas saturation of the carbonatite reservoir. Accurate quantitative gas reservoir prediction is implemented. In this method, compared with patent 201210335739.9, a lateral heterogeneity change feature of a pore structure is properly considered, and features of two types of structures, namely, a poretype structure and a fracturetype structure, are separately analyzed. This method is applicable to inversion application of a small work area, but is inapplicable to technical requirements in a large work area where lateral variations of geological features are intense and combined inversion of reservoir parameters of a plurality of wells is performed due to the following reasons: first, no work area standard template is built by combining multiwell data, to describe general features of a formation, and perform finetuning at each coordinate locations in the work area; second, a threedimensional work area template data volume cannot be manufactured, a structure is qualitatively divided merely according to a small quantity of reference wells, so that precision of description on heterogeneity is relatively low; and third, before reservoir hydrocarbon prediction, fluid sensitivity analysis is not performed on multiscale data.
In conclusion, how to overcome disadvantages in the prior art is one of the important issues that need to be resolved urgently in the field of seismic rock physics inversion technologies.
An objective of the present invention is to overcome disadvantages in the prior art to provide a seismic rock physics inversion method based on a large area tight reservoir. The present invention can effectively improve precision of hydrocarbon seismic prediction by effectively using multiwell data and multiscale waveform response data and implement quantitative prediction on a reservoir by combining a rock physics model with prestack seismic data inversion.
According to the present invention, a seismic rock physics inversion method based on a large area tight reservoir is provided, including the following specific steps.
Step 101: predicting a wave response dispersion based on a poroelasticity theory, building a multiscale rock physics model, to associate with multiscale data, where the building a multiscale rock physics model is based on impact exerted by mineral constituents, a pore structure, and a formation environment of a rock on a wave response feature of the rock, and determining that reservoir environmental factors include a temperature and a pressure, reservoir lithological factors include mineral components, a pore shape, a shale content, and a pore structure, and reservoir fluid factors include a fluid viscosity and a gaswater patchy saturation.
Step 102: analyzing and correcting a logging interpretation result based on the model and gas testing situations of some wells, analyzing fluid sensitivities of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters which are most sensitive to a porosity and a gas saturation in a plurality of observation scales, where the rock physics parameters in the two scales of acoustic logging and ultrasonic wave are elastic parameters and a combination of the elastic parameters, and the elastic parameters at least include the following physical quantities: a Pwave velocity Vp, a Swave velocity Vs, a Pwave impedance Zp, a Swave impedance Zs, a Pwave velocitytoSwave velocity ratio Vp/Vs, a Laméconstant λ, a shear modulus μ, a product λρ of a Laméconstant and a density, a product λμ of a Laméconstant and a shear modulus, a quasi pressure PR, a product μρ of a shear modulus and a density; and the analyzing fluid sensitivity includes: measuring the Pwave velocity Vp and the Swave velocity Vs in the scale of ultrasonic wave and a wave velocity during variation of saturations of gas and water, that is, a crossplot of Vp/Vs and a wave impedance.
Step 103: preferably selecting each singlewell template to manufacture a work area standard template as a singlewell rock physics template built based on each reference well data, where the work area standard template preferably uses a sensitivity parameter λρ as a vertical coordinate and the Pwave impedance as a horizontal coordinate.
Step 104: finetuning, based on lateral variations and heterogeneity of reservoir geological features, input parameters of a rock physics template at coordinates of each well according to gas testing situations of all wells in a work area, optimizing the whole work area, building a threedimensional work area rock physics template data volume, and combining the threedimensional work area rock physics template data volume with seismic prestack inversion to calculate a porosity and a saturation of a target layer; performing largearea threedimensional rock physics template parameter inversion in the whole work area, smoothing an inversion result, and finally, outputting a reservoir parameter inversion data volume, thereby implementing quantitative interpretation on the porosity and the saturation of the reservoir; and the building a threedimensional work area rock physics template data volume is cutting and sorting a tobeinverted and interpreted threedimensional seismic data volume according to project requirements, performing prestack threedimensional seismic inversion, and performing inverse calculation on the porosity and the saturation of the reservoir.
A further preferable solution of the seismic rock physics inversion method based on a large area tight reservoir provided by the present invention is:
Modeling of the building a multiscale rock physics model in step 101 includes: calculating an elastic modulus of a rock matrix and an elastic modulus of a rock skeleton, and obtaining an effective elastic modulus of the matrix by using a VoigtReussHill average equation:
where
M_{VRH }is an elastic modulus of a mineral matrix, f_{i }and M_{i }are respectively a volume fraction and an elastic modulus of an i^{th }component, N is a total quantity of mineral components; and a bulk modulus and a shear modulus of a dry rock skeleton of a dolomite are calculated by using a differential equivalent medium (DEM) theory (Mavko, 1998):
(1−y)d/dy[K*(y)]=(K_{2}−K*(y))P^{(*2)}(y) (2a), and
(1−y)d/dy[μ*(y)]=(μ_{2}−μ*(y))Q^{(*2)}(y) (2b), where
initial conditions are K*(0)=K_{1 }and μ*(0)=μ_{1}, where K_{1 }and μ_{1 }are a bulk modulus and a shear modulus (phase 1) of an initial principal mineral phase, K_{2 }and μ_{2 }are a bulk modulus and a shear modulus (phase 2) of a inclusion mineral which is gradually inserted into the host phase, y is a content of the phase 2, and P^{(*2) }and Q^{(*2) }are related to a shape of the embedded inclusions.
Modeling of the building a multiscale rock physics model in step 101 further includes considering a rock in a reservoir environment and estimating densities and bulk moduli of natural gas of a reservoir fluid under different temperature and pressure conditions by using a van der Waals equation.
Modeling of the building a multiscale rock physics model in step 101 further includes: considering heterogeneous distribution of a pore fluid, ignoring heterogeneity of a pore structure, predicting Pwave and Swave velocities of a fluid saturated rock by using a BiotRayleigh equation, and in addition, further considering impact of elastic wave velocity dispersion, to implement fusion between multidisciplinary data in different scales, where a specific form of the BiotRayleigh equation is as follows:
where
u=[u_{1}, u_{2}, u_{3}], U^{(1)}=[U_{1}^{(1)}, U_{2}^{(1)}, U_{3}^{(1)}], and U^{(2)}=[U_{1}^{(2)}, U_{2}^{(2)}, U_{3}^{(2)}] respectively denote space vector of displacements of three components (rock skeleton, a fluid 1, and a fluid 2), and subscripts 1, 2, and 3 denote three directions of a vector space; ζ denotes a local fluid deformation increment induced by the process of seismic wave propagation, and e_{ij}, ξ_{ij}^{(1)}, and ξ_{ij}^{(2) }are as follows:
where
x1, x2, and x3 respectively denote coordinates in the three directions; φ_{1 }and φ_{2 }denote absolute porosities of two types of pores, and a total porosity of a rock is ϕ=ϕ_{1}+ϕ_{2}; φ_{10 }and φ_{20 }respectively denote local porosities in two areas. If a rock merely includes a type of skeleton inside, but saturated with two immiscible fluids, ϕ_{10}=ϕ_{20}=ϕ; assuming that φ_{1 }represents watersaturated pores (background/host phase fluid), and φ_{2 }represents gassaturated pores (inclusion/patchy phase fluid), φ_{1}/φ is a water saturation, and φ_{2}/φ is a gas saturation; ρ_{f1 }and η_{1 }denote a density and a viscosity of a background phase fluid, and ρ_{f2 }and η_{2 }denote a density and a viscosity of an inclusion phase fluid; R_{0 }refers to the gas pocket radius, and κ_{10 }denotes a rock permeability; and the mathematic determination equation of the elastic parameters A, N, Q_{1}, R_{1}, Q_{2}, and R_{2}, density parameters ρ_{11}, ρ_{12}, ρ_{13}, ρ_{22}, and ρ_{33}, and dissipation parameters b_{1 }and b_{2 }are provided.
Step 102 further includes performing comparison and analysis to determine that laws and orders of sensitivities of rock physics parameters in an ultrasonic wave scale and a logging scale are basically consistent and that parameters that are most sensitive to a pore fluid are λ and λρ.
In step 103, correcting horizontal and vertical coordinates of a lattice of the work area standard rock physics template means to ensure that description results of the work area standard rock physics template basically cover all pieces of data of a standard well, so that the corrected work area standard rock physics template is expressed as:
Assuming that each grid point position at the singlewell rock physics template can be expressed by (Mk(i, j), Nk(i, j)) according to its coordinates in 2D crossplot, where i and j respectively correspond to the gradual changes of porosity and saturation (i=1, 2 . . . 11 corresponds to that the gradual porosity from 0.02 to 0.12; and j=1, 2 . . . 11 corresponds to that the gradual saturation from 0 to 100%), k denotes a k^{th }reference well, and a value (M_{s}(i, j), N_{s}(i, j)) at each grid point position of the standard template may be expressed as:
where
A (k) denotes a weight of the k^{th }well, and B(i, j) and C(i, j) respectively denote corrections performed on the horizontal and vertical coordinates of lattices of the work area standard rock physics template at a template lattice corresponding to i and j based on integrated reference data of respective wells.
The reservoir parameter rock physics inversion in step 104 is performing seismic inversion and fluid detection tests at locations of respective wells based on the work area standard rock physics template, where a specific method includes:
Extracting a twodimensional well through line from the threedimensional seismic data volume, estimating reservoir and fluid parameters of a target layer near each well location, the results are compared with the known drilling and gas production data of the wells. The template is adjust to assure inversion results and interpretation conclusion being fully consistent with known data; and the seismic inversion template by debugging the standard template through a 2D seismic inversion test near the kth well can be expressed as (M′_{k}(i, j), N′_{k}(i, j)).
In the work area, based on the seismic inversion template (M′_{k}(i, j), N′_{k}(i, j)) of each well, optimizing the whole work area, and generating a threedimensional data volume of a work area rock physics model, where specifically, there is an independent seismic rock physics model corresponding to each coordinate location (x, y) in the work area, and a template thereof (M_{3D}(x, y, i, j), N_{3D}(x, y, i, j)) is determined based on the seismic inversion template of the location of each well:
wherein
(x_{k}, y_{k}) are coordinates of the kth well, L is a total number of wells, and Q(x, y, k) is a weight coefficient of the kth well which is used for calculating a template at the coordinates (x, y) in the work area and may be determined by using the following equation:
where
based on the foregoing method, the observed data at each well can be taken into account, and seismic inversion and interpretation of the reservoir parameters are controlled based on logging observation at each geographic location, and the closer spatial distance from the inversion location to a reference well leads to the more remarkable impact from the control of the well; (M_{3D}(x, y, i, j), N_{3D}(x, y, i, j)), that is, in a manufacturing process, a work area rock physics model threedimensional data volume first moves along an xline direction in a seismic data .sgy standard format, and then, is processed along an inline direction one xline by one xline.
In step 104, the porosity and saturation of the inversion are smoothed by using a weighted averaging method, to weaken impact of the outliers of the inversion/interpretation data, where assuming that a target point is closer, impact of the inversion result on the target point is greater, and three types of weighted templates are defined according to twodimensional normal distribution, as shown in equation (7); T_{1 }and T_{2 }are evolved from twodimensional Gaussian discrete templates, T_{3 }is a twodimensional Gaussian template of a 3×3 field, a greatest weight in the templates is a location of the target point, and the templates may be properly adjusted according to a location of minimum uniformity in the neighborhood to form a template related to the neighborhood:
using T_{1 }as an example, twodimensional inversion section data (i, j) is smoothed inside the neighborhood, and a specific algorithm may be expressed as:
where
data_{5 }is the numerical value at the target position after smoothing.
An implementation principle of the present invention is that: the present invention includes: predicting a wave response dispersion based on a poroelasticity theory, and building a multiscale rock physics model, to associate with multiscale data; analyzing and correcting a logging interpretation result based on the model and gas testing situations of some wells, analyzing fluid sensitivities of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters which are most sensitive to a porosity and a gas saturation in a plurality of observation scales; preferably selecting each singlewell template to manufacture a work area standard template as a singlewell rock physics template built based on each piece of reference well data; and finetuning, based on lateral variations and heterogeneity of reservoir geological features, input parameters of a rock physics template at coordinates of each well according to gas testing situations of all wells in a work area, optimizing the whole work area, building a threedimensional work area rock physics template data volume, and combining the threedimensional work area rock physics template data volume with seismic prestack inversion to calculate rock physics parameters in the large work area.
Compared with the prior art, the present invention has the following significant advantages:
First, the present invention initiates a seismic rock physics inversion method based on a large area tight reservoir, and has an important practical meaning of promotion and application in a large area.
Second, the present invention can effectively improve precision of hydrocarbon seismic prediction by effectively using multiwell data and multiscale waveform response data and implement quantitative prediction on a reservoir by combining a rock physics model with prestack seismic data inversion.
Third, in the present invention, multiscale fluid sensitivity analysis is performed on rock physics parameters, where based on multiscale observation, the most sensitive petrophysical parameters are selected for reservoir hydrocarbon prediction.
Fourth, a standard template of a target layer of a work area is built by combining multiwell data and can describe general geographic and rock physics features of the target layer, the template is further used for performing seismic inversion tests on a known well, to build a threedimensional rock physics template data volume, and lateral heterogeneous variations are considered on the basis of general geographic features, so that the present invention is application to rock physics inversion of seismic parameters in a large work area.
Specific implementations of the present invention are further described below in detail with reference to the accompanying drawings and embodiments.
As shown in
Step 101: predicting a wave response dispersion based on a poroelasticity theory, building a multiscale rock physics model, to associate with multiscale data, where the building a multiscale rock physics model is based on impact exerted by mineral constituents, a pore structure, and a formation environment of a rock on a wave response feature of the rock, and determining that reservoir environmental factors include a temperature and a pressure, reservoir lithological factors include mineral components, a pore shape, a shale content, and a pore structure, and reservoir fluid factors include a fluid viscosity and a gaswater patchy saturation.
Step 102: analyzing and correcting a logging interpretation result based on the model and gas testing situations of some wells, analyzing fluid sensitivities of rock physics parameters in two scales of acoustic logging and ultrasonic wave, and sifting the rock physics parameters which are most sensitive to a porosity and a gas saturation in a plurality of observation scales, where the rock physics parameters in the two scales of acoustic logging and ultrasonic wave are elastic parameters and a combination of the elastic parameters, and the elastic parameters at least include the following physical quantities: a Pwave velocity Vp, a Swave velocity Vs, a Pwave impedance Zp, a Swave impedance Zs, a Pwave velocitytoSwave velocity ratio Vp/Vs, a Laméconstant k, a shear modulus μ, a product λρ of a Laméconstant and a density, a product λμ of a Laméconstant and a shear modulus, a quasi pressure PR, a product μρ of a shear modulus and a density; and the analyzing fluid sensitivity includes: measuring the Pwave velocity Vp and the Swave velocity Vs in the scale of ultrasonic wave and a wave velocity during variation of saturations of gas and water, that is, a crossplot of Vp/Vs and a wave impedance.
Step 103: preferably selecting each singlewell template to manufacture a work area standard template as a singlewell rock physics template built based on each piece of reference well data, where the work area standard template preferably uses a sensitivity parameter λρ as a vertical coordinate and the Pwave impedance as a horizontal coordinate.
Step 104: finetuning, based on lateral variations and heterogeneity of reservoir geological features, input parameters of a rock physics template at coordinates of each well according to gas testing situations of all wells in a work area, optimizing the whole work area, building a threedimensional work area rock physics template data volume, and combining the threedimensional work area rock physics template data volume with seismic prestack inversion to calculate a porosity and a saturation of a target layer; performing largearea threedimensional rock physics template parameter inversion in the whole work area, smoothing an inversion result, and finally, outputting a reservoir parameter inversion data volume, thereby implementing quantitative interpretation on the porosity and the saturation of the reservoir; and the building a threedimensional work area rock physics template data volume is cutting and sorting a tobeinverted and interpreted threedimensional seismic data volume according to project requirements, performing prestack threedimensional seismic inversion, and performing inverse calculation on the porosity and the saturation of the reservoir.
According to the embodiments of the present invention, in the seismic rock physics inversion method based on a large area tight reservoir, with regard to a strong heterogeneity feature of a carbonatite reservoir, a mineral composition of the reservoir is analyzed, a dry rock skeleton model of the reservoir is built, and according to an environment of the reservoir, a reservoir fluid model is built, and a multiscale rock physics model is constructed; and based on the multiscale rock physics model, an industrialization technology procedure of rock physics inversion on a large work area reservoir and fluid parameters is provided.
According to the embodiments of the present invention, in the seismic rock physics inversion method based on a large area tight reservoir, first, logging data analysis and precise interpretation are performed, and a singlewell rock physics model and a template are manufactured; second, rock physics parameter fluid sensitivity analysis in sonic log and an ultrasonic wave scale are performed. Results show that: with a reduction of a porosity, sensitivities of respective parameters are obviously reduced, but an order of the sensitivities of the parameter is basically unchanged; and orders of sensitivities of rock physics parameters in the two scales are basically consistent, but one parameter has different sensitivities to a pore fluid in different observation scales. Parameters λρ and λ that are most sensitive to a gas saturation are preferably selected based on multiscale sensitivity analysis.
According to the embodiments of the present invention, in the seismic rock physics inversion method based on a large area tight reservoir, to describe a general law of geological features of a target layer, each singlewell simulation result is preferably selected to manufacture a work area standard rock physics template, the work area standard rock physics template is combined with a seismic inversion test of each well through twodimensional line to manufacture a threedimensional rock physics model data volume in a large work area, the threedimensional rock physics model data volume is combined with seismic prestack inversion to estimate a porosity and a gas saturation of a reservoir, and a smoothing matrix is used for smoothing an inversion result data volume. Comparisons between inversion results and a logging interpretation and a well testing conclusion of a target layer show that the predicted results match an actual formation porosity and an actual natural gas production capacity well.
According to the embodiments of the present invention, in the seismic rock physics inversion method based on a large area tight reservoir, with reference to a rock physics analysis, an industrialization technology procedure of seismic quantitative prediction on a large work area reservoir and fluid parameters has been researched and developed and is successfully applied to a tight dolomite reservoir in West China. In consideration of differences in geological features, reservoir types, and fluid distribution situations of respective work areas, to ensure applicability and accuracy of the rock physics model, an actual situation of a reservoir needs to be taken as a starting point, analysis is performed for different rock lithological properties, different pore structures, and different fluids, and correction is performed with reference to experimental data, logging, and seismic inversion data, so as to effectively apply the seismic rock physics inversion method.
A tight dolomite gas reservoir in the Sichuang Basin is used as an example to describe an implementation process of the seismic rock physics inversion method based on a large area tight reservoir rock.
As shown in
As shown in
The comparison shows that laws and orders of sensitivities of rock physics parameters in the two scales are basically consistent and parameters that are most sensitive to a pore fluid are k and λρ. Sensitivities of a few parameters to the fluid are slightly changed in different observation scales, for example, is most insensitive to the pore fluid in the ultrasonic wave scale, but its sensitivity to the fluid is increased in a sonic logging scale. Changes between the scales increase difficulty in reservoir fluid recognition. By means of the foregoing comparison and analysis, parameters λ and λρ that are most sensitive to the fluid in two observation scales are preferably selected as a basis of subsequent reservoir prediction and fluid.
As shown in
As shown in
Descriptions not included in the specific implementations of the present invention are wellknown technologies in the art and can be carried out by referring to wellknown technologies.
The present invention is verified by repetitious experiments, and satisfying trial results are achieved.
The foregoing specific implementations and embodiments specifically support the technical concept of the seismic rock physics inversion method based on a large area tight reservoir provided by the present invention, and cannot be used to limit a protection scope of the present invention. Any equivalent changes or equivalent modifications made on the basis of the present technical solution according to the technical concept provided in the present invention all fall within the protection scope of the technical solution of the present invention.