CN104459777A - Fluid identification method and system based on fluid bulk modulus AVO inversion - Google Patents

Abstract

The invention provides a fluid identification method and system based on fluid bulk modulus AVO inversion. The method includes the steps of collecting pre-stack seismic data, logging data and geological finding data of a target reservoir, building an AVO approximation formula representing a fluid bulk modulus, extracting wavelets according to the pre-stack seismic data, the logging data, the geological finding data and the AVO approximation formula representing the fluid bulk modulus, determining a fluid bulk modulus data body according to the pre-stack seismic data, the logging data, the geological finding data and the wavelets, and recognizing the type of fluid in current reservoir gaps according to the fluid bulk modulus data body. AVO inversion is performed through the AVO approximation formula representing the fluid bulk modulus so that fluid bulk modulus parameters can be estimated, fluid recognition illusion is avoided, and reliability of reservoir gap fluid type prediction is improved.

Description

Based on the method and system of the fluid identification of fluid modulus AVO inverting

Technical field

The present invention, about field of petroleum geophysical exploration, particularly about the inversion technique of pre-stack seismic, is a kind of method and system of the fluid identification based on fluid modulus AVO inverting concretely.

Background technology

From 20 century 70s, due to the develop rapidly of seismic technology digitizing and computer technology, utilize wave mechanics problem to carry out study hotspot that reservoir prediction and fluid identification become petroleum industrial circle.Wherein, AVO (AmplitudeVersus Offset, the change of amplitude offset distance) inversion technique is as Changing Pattern according to amplitude offset distance prediction subsurface lithologic and the mainstream technology containing fluid properties, its core concept extracts the elastic parameter of demand by research reflection coefficient with the Changing Pattern of incident angle, and theoretical foundation describes the Zoeppritz equation of plane wave in horizontal surface reflections and transmission.Owing to belonging to Nonlinear inverse problem based on the parameter extraction of Zoeppritz equation, counting yield is low and constrain its application in actual production by problems such as noise effect are large.

In order to overcome the reflection coefficient complex forms derived by Zoeppritz equation and the difficulty of not easily carrying out numerical evaluation, many scholars simplify Zoeppritz equation.Original 7 Independent Variables for Simplifyings are 5 independent variables by Koefoed; Bortfeld discusses the plane longitudinal wave reflection coefficient approximate calculation method of vertical incidence in detail, and gives the reduced equation distinguishing fluid and solid; Aki and Richards, when supposing that adjacent earth formations dielectric resilient Parameters variation is less, gives the longitudinal wave reflection coefficient linear-apporximation formula comprising p-and s-wave velocity and density relative variation.On this basis, many scholars have carried out again deriving, concluding to Aki-Richards equation, propose the longitudinal wave reflection coefficient represented with different elastic parameter respectively.Wherein, Shuey gives the relative reflectance approximate expression form of outstanding Poisson ratio; The people such as Fatti give and change with Relative Wave Impedance the reflection coefficient approximate formula represented; Mallick gives the reflection coefficient represented by ray parameter approximate form; Goodway has derived the reflection coefficient approximate formula represented with Lame parameter relative variation.

Along with going deep into of petroleum exploration and development, the focus becoming research containing fluid identification problem of subsurface reservoir, in the urgent need to extracting the parameter of more characteristic of fluid that can reflect in underground medium from seismic data.The people such as Russell recombinate to Aki-Richards is approximate in conjunction with saturated fluid poroelastic medium is theoretical, propose the Russell reflection coefficient approximate formula comprising Gassmann fluid item f, give prominence to and embody the impact of blowhole hydrodynamic effect on reflection coefficient, promoted the development of the fluid identification technology based on AVO inverting.But due to the solid-liquid coupling characteristic of subsurface rock, the elastic parameter that present stage is estimated based on AVO inversion method is (as wave impedance, Lame's constant, Gassmann fluid item etc.) all can be subject to rock solid effect (Rock Matrix, factor of porosity etc.) impact generation fluid identification illusion, reduce the reliability of geological condition complex area reservoir petroleuon-gas prediction.

Therefore, in order to effectively improve reservoir fluid characterization susceptibility and the fluid identification reliability of geological condition complex area, be badly in need of in prior art a kind of comprise to pore fluid information more the reflection coefficient approximate formula of sensibility elasticity parameter and corresponding AVO inversion method to identify reservoir fluid.

Summary of the invention

The Rock Elastic Parameters based on conventional AVO approximate estimation existed to overcome prior art easily produces reservoir by solid-liquid coupling properties influence and sentences the problem knowing illusion containing fluid, the invention provides a kind of method and system of the fluid identification based on fluid modulus AVO inverting, fluid modulus parameters separated is realized in reflection coefficient is approximate, fluid modulus is more responsive to reservoir fluid information, utilize the AVO approximate formula characterizing fluid modulus to carry out AVO inverting and can estimate fluid modulus parameter, avoid fluid identification illusion, improve reservoir pore space fluid type forecasting reliability.

An object of the present invention is, provides a kind of method of the fluid identification based on fluid modulus AVO inverting, comprising: gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data; Build the AVO approximate formula characterizing fluid modulus; AVO approximate formula equation according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet; According to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume; According to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

An object of the present invention is, provides a kind of system of the fluid identification based on fluid modulus AVO inverting, comprising: data collection device, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data; Approximate formula construction device, for building the AVO approximate formula characterizing fluid modulus; Wavelet extraction device, extracts wavelet for the AVO approximate formula equation according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus; Fluid modulus data volume determining device, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume; Fluid type recognition device, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

Beneficial effect of the present invention is, provide a kind of method and system of the fluid identification based on fluid modulus AVO inverting, Rock Elastic Parameters based on conventional AVO approximate estimation easily produces reservoir by solid-liquid coupling properties influence and sentences knowledge illusion containing fluid, the present invention is based on poroelasticity MEDIUM THEORY and Critical porosity model, fluid modulus parameters separated is realized in reflection coefficient is approximate, fluid modulus is more responsive to reservoir fluid information, and eliminate the fluid identification illusion that the solid effects such as reservoir rock factor of porosity cause to greatest extent, utilize the AVO approximate formula characterizing fluid modulus to carry out AVO inverting and can estimate fluid modulus parameter, avoid fluid identification illusion, improve reservoir pore space fluid type forecasting reliability.

For above and other object of the present invention, feature and advantage can be become apparent, preferred embodiment cited below particularly, and coordinate institute's accompanying drawings, be described in detail below.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

The process flow diagram of the embodiment one of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 1 provides for the embodiment of the present invention;

The process flow diagram of the embodiment two of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 2 provides for the embodiment of the present invention;

The process flow diagram of the embodiment three of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 3 provides for the embodiment of the present invention;

The process flow diagram of the embodiment four of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 4 provides for the embodiment of the present invention;

Fig. 5 is the particular flow sheet of the step S103 in Fig. 1;

Fig. 6 is the particular flow sheet of the step S104 in Fig. 1;

The structured flowchart of the embodiment one of the system of a kind of fluid identification based on fluid modulus AVO inverting that Fig. 7 provides for the embodiment of the present invention;

The structured flowchart of the embodiment two of the system of a kind of fluid identification based on fluid modulus AVO inverting that Fig. 8 provides for the embodiment of the present invention;

The structured flowchart of the embodiment three of the system of a kind of fluid identification based on fluid modulus AVO inverting that Fig. 9 provides for the embodiment of the present invention;

The structured flowchart of the embodiment four of the system of a kind of fluid identification based on fluid modulus AVO inverting that Figure 10 provides for the embodiment of the present invention;

The concrete structure block diagram of the wavelet extraction device 300 in the system of a kind of fluid identification based on fluid modulus AVO inverting that Figure 11 provides for the embodiment of the present invention;

The concrete structure block diagram of the fluid modulus data volume determining device 400 in the system of a kind of fluid identification based on fluid modulus AVO inverting that Figure 12 provides for the embodiment of the present invention;

Figure 13 is pore fluid type is in the gentle situation of water, and velocity of longitudinal wave is with the changing trend diagram of factor of porosity and water saturation;

Figure 14 is pore fluid type is in the gentle situation of water, and Gassmann fluid item is with the changing trend diagram of factor of porosity and water saturation;

Figure 15 is pore fluid type is in the gentle situation of water, and fluid modulus is with the changing trend diagram of factor of porosity and water saturation;

Figure 16 is layer model curve synoptic diagram one-dimensionally;

Prestack CMP road collection schematic diagram when Figure 17 is non-plus noise;

Figure 18 is the inversion result schematic diagram that prestack CMP road collection when utilizing non-plus noise carries out inverting and obtains;

The prestack CMP road collection schematic diagram of Figure 19 to be signal to noise ratio (S/N ratio) be 1:1;

Figure 20 is the inversion result schematic diagram that the prestack CMP road collection utilizing signal to noise ratio (S/N ratio) to be 1:1 carries out inverting and obtains;

Figure 21 is the superposition seismic section schematic diagram of research survey line;

Figure 22 is the fluid modulus K of estimation _fdiagrammatic cross-section.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

Due to the solid-liquid coupling characteristic of subsurface rock, the elastic parameter that present stage is estimated based on AVO inversion method is (as wave impedance, Gassmann fluid item etc.) all can be subject to rock solid effect (Rock Matrix, factor of porosity etc.) impact generation fluid identification illusion, reduce the reliability of geological condition complex area reservoir petroleuon-gas prediction.The present invention is based on poroelasticity MEDIUM THEORY and the new AVO approximate formula of Critical porosity model inference, in reflection coefficient be approximate, realize fluid modulus parameters separated, carry out AVO inverting based on new approximate formula and can obtain the elastic parameter more responsive to reservoir fluid information---fluid modulus.

Fig. 1 is the particular flow sheet of the embodiment one of the method for a kind of fluid identification based on fluid modulus AVO inverting that the present invention proposes, in order to improve the stability of fluid modulus estimation, the present invention is based on bayesian theory and set up inversion objective function, utilize heavy weighted least-squares iterative algorithm loop iteration to solve objective function, realize the quantitative estimation of earthquake scale fluid modulus.As shown in Figure 1, in embodiment one, described method comprises:

S101: gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

S102: build the AVO approximate formula characterizing fluid modulus.

AVO (Amplitude Versus Offset, the change of amplitude offset distance) approximate formula is the basis of carrying out AVO inverting, the present invention is based on poroelasticity MEDIUM THEORY and Critical porosity model, derive the AVO approximate formula of sign fluid modulus obtained, it is provide theoretical foundation based on the fluid identification of AVO inverting.

The people such as Russell from Aki-Richards approximate formula, the reflectance signature approximate formula of outstanding reservoir fluid feature of having derived:

$R_{\mathrm{PP}}\left(\mathrm{\θ}\right)=\left[(1-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{{\mathrm{\γ}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\θ}}{4}\right]\frac{\mathrm{\Δf}}{f}+[\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ\μ}}{\mathrm{\μ}}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\θ}}{4}]\frac{\mathrm{\Δ\ρ}}{\mathrm{\ρ}}---\left(1\right)$

The people such as Dehua Han propose the experimental formula of Gassmann fluid item:

f＝G(φ)K _f(2)

Wherein, $G\left(\mathrm{\φ}\right)=\frac{{(1-K_n)}^2}{\mathrm{\φ}}{K}_n=\frac{K_{\mathrm{dry}}}{K_m}$

Formula (2) is substituted into formula (1), and considers modulus of shearing not by the impact of pore fluid, utilize dry Shear Modulus of Rock in Situ μ _dryreplace μ, carry out corresponding conversion, can obtain:

$R_{\mathrm{PP}}\left(\mathrm{\θ}\right)=\left[(1-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{{\mathrm{\γ}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\θ}}{4}\right]\frac{\mathrm{\Δ}\left(G\left(\mathrm{\φ}\right)K_f\right)}{G\left(\mathrm{\φ}\right)K_f}+[\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ\μ}}{\mathrm{\μ}}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\θ}}{4}]\frac{\mathrm{\Δ\ρ}}{\mathrm{\ρ}}---\left(3\right)$

The Critical porosity model that Nur proposes, expression formula is shown below:

$\left\{\begin{array}{c}{K}_{\mathrm{dry}}=K_m(1-\frac{\mathrm{\φ}}{{\mathrm{\φ}}_c})\\ {\mathrm{\μ}}_{\mathrm{dry}}={\mathrm{\μ}}_m(1-\frac{\mathrm{\φ}}{{\mathrm{\φ}}_c})\end{array}\right.---\left(4\right)$

Wherein, φ _crepresent Critical porosity, K _dryrepresent the bulk modulus of dry rock, μ _dryrepresent the modulus of shearing of dry rock, K _mrepresent the bulk modulus of solid mineral matrix, μ _mrepresent the modulus of shearing of mineral substrate.

Launch further to obtain to formula (3) in conjunction with Nur formula (4):

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\θ}\right)=\left[(1-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{{\mathrm{\γ}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\θ}}{4}\right](\frac{\mathrm{\ΔG}\left(\mathrm{\φ}\right)}{G\left(\mathrm{\φ}\right)}+\frac{\mathrm{\Δ}{K}_f}{K_f})+[\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}](\frac{\mathrm{\Δ}{\mathrm{\μ}}_m}{{\mathrm{\μ}}_m}+\frac{\mathrm{\Δ}({\mathrm{\φ}}_c-\mathrm{\φ})}{{\mathrm{\φ}}_c-\mathrm{\φ}})\\ +[\frac{1}{2}-\frac{{\sec }^2\mathrm{\θ}}{4}]\frac{\mathrm{\Δ\ρ}}{\mathrm{\ρ}}\end{array}---\left(5\right)$

Will substitute into G (φ), launch further to obtain:

$\left.\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\θ}\right)=\left[(1-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{{\mathrm{\γ}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\θ}}{4}\right]\frac{\mathrm{\Δ}{K}_f}{K_f}[+\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ}{\mathrm{\μ}}_m}{{\mathrm{\μ}}_m}+[\frac{{\sec }^2\mathrm{\θ}}{4}-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{2{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}+\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ\φ}}{\mathrm{\φ}}\\ +[\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ\φ}({\mathrm{\φ}}_c-\mathrm{\φ})}{\mathrm{\φ}({\mathrm{\φ}}_c-\mathrm{\φ})}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\θ}}{4}]\frac{\mathrm{\Δ\ρ}}{\mathrm{\ρ}}\end{array}\right]---\left(6\right)$

Make f _m=φ μ, and utilize formula (4), the AVO approximate formula of the final sign fluid modulus built is as follows:

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\θ}\right)=\left[(1-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{{\mathrm{\γ}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\θ}}{4}\right]\frac{\mathrm{\Δ}{K}_f}{K_f}+[\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{4{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}-\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ}]\frac{\mathrm{\Δ}\left(f_m\right)}{f_m}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\θ}}{4}]\frac{\mathrm{\Δ\ρ}}{\mathrm{\ρ}}\\ +(\frac{{\sec }^2\mathrm{\θ}}{4}-\frac{{\mathrm{\γ}}_{\mathrm{dry}}^2}{2{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\θ}+\frac{2}{{\mathrm{\γ}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\θ})\frac{\mathrm{\Δ\φ}}{\mathrm{\φ}}\end{array}---\left(7\right)$

Wherein, f _m=φ μ is the solid item of subsurface rock, and θ is incident angle, K _ffor the fluid modulus of subsurface rock, f _mfor the solid item of subsurface rock, φ is the factor of porosity of subsurface rock, and ρ is the density of subsurface rock, and μ is the modulus of shearing of subsurface rock, △ K _ffor the difference of the fluid modulus of both sides, interface, △ f _mfor the difference of both sides, interface solid item, △ ρ is the difference of the density of both sides, interface, and △ φ is the difference of the factor of porosity of both sides, interface, for dry rock P-S wave velocity ratio square, for saturated rock P-S wave velocity ratio square.

S103: the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet.Fig. 5 is the particular flow sheet of step S103.

S104: according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Fig. 6 is the particular flow sheet of step S104.

S105: according to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

The process flow diagram of the embodiment two of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 2 provides for the embodiment of the present invention, as shown in Figure 2, in embodiment two, the method specifically comprises:

S201: gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

S202: carry out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road collection (i.e. common midpoint gather) data.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

S203: build the AVO approximate formula equation characterizing fluid modulus.

S204: the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet.Fig. 5 is the particular flow sheet of step S204.

S205: according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Fig. 6 is the particular flow sheet of step S205.

S206: according to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

The process flow diagram of the embodiment three of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 3 provides for the embodiment of the present invention, as shown in Figure 3, in embodiment three, the method specifically comprises:

S301: gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

S302: carry out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road set information.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

S303: environmental correction is carried out to described well-log information;

S304: singular value elimination is carried out to the well-log information after environmental correction;

S305: dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of determining described object reservoir according to the well-log information after singular value is eliminated.In concrete embodiment, full wave train log is carried out in exploration work area, the well-log information obtained, as prior imformation, needs, after the pre-service such as environmental correction, singular value elimination, to calculate dry rock P-S wave velocity ratio γ in conjunction with rock physics experimental formula or experiment statistics result _dry, saturated rock P-S wave velocity ratio γ _satnumerical value.

S306: determine the fluid modulus curve corresponding with described well-log information and modulus of shearing curve according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.In a particular embodiment, fluid modulus is K _f, modulus of shearing is μ curve.

S307: build the AVO approximate formula equation characterizing fluid modulus.

S308: the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet.Fig. 5 is the particular flow sheet of step S308.

S309: according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Fig. 6 is the particular flow sheet of step S309.

S310: according to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

The process flow diagram of the embodiment four of the method for a kind of fluid identification based on fluid modulus AVO inverting that Fig. 4 provides for the embodiment of the present invention, as shown in Figure 4, in embodiment four, the method specifically comprises:

S401: gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

S402: carry out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road set information.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

S403: environmental correction is carried out to described well-log information;

S404: singular value elimination is carried out to the well-log information after environmental correction;

S405: dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of determining described object reservoir according to the well-log information after singular value is eliminated.In concrete embodiment, full wave train log is carried out in exploration work area, the well-log information obtained, as prior imformation, needs, after the pre-service such as environmental correction, singular value elimination, to calculate dry rock P-S wave velocity ratio γ in conjunction with rock physics experimental formula or experiment statistics result _dry, saturated rock P-S wave velocity ratio γ _satnumerical value.

S406: determine the fluid modulus curve corresponding with described well-log information and modulus of shearing curve according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.In a particular embodiment, fluid modulus is K _f, modulus of shearing is μ curve.

S407: according to described Prestack seismic data, well-log information, Geological Achievements data, meticulous tracing of horizons is carried out to object reservoir, obtain seismic horizon data.

In a particular embodiment, in conjunction with the geologic background in work area, meet on the basis of work area geologic sedimentation pattern and Sequence Stratigraphic Formation in guarantee zone of interest position, fine geology explanation is carried out to the zone of interest of research, dark relation when explaining that the seismic horizon data obtained not only is used for identifying, also for setting up the model constrained of refutation process.

S408: build the AVO approximate formula equation characterizing fluid modulus.

S409: the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet.Fig. 5 is the particular flow sheet of step S409.As shown in Figure 5, this step specifically comprises:

S501: the density and the factor of porosity that extract subsurface rock from described well-log information.In a particular embodiment, the density of subsurface rock is represented by ρ, and the factor of porosity of subsurface rock is represented by φ.

S502: according to the solid item of described modulus of shearing curve and described factor of porosity determination subsurface rock, in a particular embodiment, the solid item of subsurface rock passes through f _mrepresent, then f _m=φ μ.

S503: extract wavelet according to the density of described subsurface rock, solid item, factor of porosity, fluid modulus curve, the AVO approximate formula characterizing fluid modulus, prestack CMP road collection and seismic horizon data.

As shown in Figure 4, in embodiment four, the method also comprises:

S410: according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume.Fig. 6 is the particular flow sheet of step S410.As shown in Figure 6, this step specifically comprises:

S601: prestack CMP road collection, well-log information, Geological Achievements data and wavelet described in utilization, based on bayesian theory, use gauss of distribution function is likelihood function, Cauchy is distributed as and prior-constrainedly sets up AVO inversion objective function.The AVO inversion objective function set up is:

(G ^ΤG+ηQ+αC ^ΤC)m＝G ^Τd+αC ^Τξ (8)

$\mathrm{\η}=\mathrm{\λ}\frac{{\mathrm{\σ}}_n^2}{{\mathrm{\σ}}_m^2}$

$\mathrm{\ξ}=\frac{1}{2}\ln \left(\frac{M}{M_0}\right)$

Wherein, for the variance of noise in CMP road set information, for the variance of elastic parameter relative variation, λ, α are weighting coefficient, and m is the elastic parameter relative variation matrix treating inverting, and G is for just to calculate submatrix, and C is integration matrix, and d is CMP road collection matrix, and Q is diagonally opposing corner weighting matrix, and M is model constrained matrix, M ₀for the average of M.

S602: utilize heavy weighted least-squares iterative algorithm to solve described AVO inversion objective function, obtain the relative variation of fluid modulus.In a particular embodiment, this step specifically comprises:

(1) initial reflection coefficient sequence (initial model) m, is set up ₀;

(2), according to the quality of seismic data, suitable weighting coefficient λ, α is selected;

(3), G is calculated according to prior imformation, model data and log data ^tg, G ^Τd, C ^Τc, C ^Τξ, utilizes the inversion result m of kth-1 iteration _k-1(iteration utilizes initial model m for the first time ₀) calculate η and Q;

(4), to formula (8) carry out inversion calculation, obtain kth time inversion result:

m _k＝(G ^ΤG+ηQ+αC ^ΤC) ^-1(G ^Τd+αC ^Τξ)

In other embodiments of the present invention, in addition to the foregoing steps, the following condition of convergence can also be designed:

$\frac{|J\left(m_k\right)-J\left(m_{k-1}\right)|}{\left(\right|J\left(m_k\right)|+|J\left(m_{k-1}\right)\left|\right)/2}<e$

_efor convergence error.Utilize m _kcalculate target function value J (m _k), the termination of iterations when meeting the above-mentioned condition of convergence, when not meeting the condition of convergence, rebound (2) step, iteration proceeds.

S603: utilize trace integral thought that described relative variation is converted into fluid modulus data volume.

As shown in Figure 4, in embodiment four, the method also comprises:

S411: according to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

After estimation obtains fluid modulus data volume, contrast with the theoretical value of reservoir fluid bulk modulus, namely can identify the type of fluid in reservoir pore space.

As mentioned above, be the method for a kind of fluid identification based on fluid modulus AVO inverting provided by the invention, achieve the fluid modulus parameter estimation being separated AVO approximate formula based on fluid modulus, fluid modulus parameter is high containing fluid type susceptibility to reservoir, and eliminate the fluid identification illusion that the solid effects such as reservoir rock factor of porosity cause to greatest extent, improve reservoir pore space fluid type forecasting reliability.

Fig. 7 is the concrete structure block diagram of the embodiment one of the system of a kind of fluid identification based on fluid modulus AVO inverting that the present invention proposes, in order to improve the stability of fluid modulus estimation, the present invention is based on bayesian theory and set up inversion objective function, utilize heavy weighted least-squares iterative algorithm loop iteration to solve objective function, realize the quantitative estimation of earthquake scale fluid modulus.As shown in Figure 7, in embodiment one, described system comprises:

Data collection device 100, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

Approximate formula construction device 200, for building the AVO approximate formula characterizing fluid modulus.

AVO (Amplitude Versus Offset, the change of amplitude offset distance) approximate formula is the basis of carrying out AVO inverting, the present invention is based on poroelasticity MEDIUM THEORY and Critical porosity model, derive the AVO approximate formula of sign fluid modulus obtained, it is provide theoretical foundation based on the fluid identification of AVO inverting.

The people such as Russell from Aki-Richards approximate formula, the reflectance signature approximate formula of outstanding reservoir fluid feature of having derived:

$R_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{\mathrm{\&Delta;f}}{f}+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;\&mu;}}{\mathrm{\&mu;}}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}---\left(1\right)$

The people such as Dehua Han propose the experimental formula of Gassmann fluid item:

f＝G(φ)K _f(2)

Wherein, $G\left(\mathrm{\&phi;}\right)=\frac{{(1-K_n)}^2}{\mathrm{\&phi;}}{K}_n=\frac{K_{\mathrm{dry}}}{K_m}$

Formula (2) is substituted into formula (1), and considers modulus of shearing not by the impact of pore fluid, utilize dry Shear Modulus of Rock in Situ μ _dryreplace μ, carry out corresponding conversion, can obtain:

$R_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{\mathrm{\&Delta;}\left(G\left(\mathrm{\&phi;}\right)K_f\right)}{G\left(\mathrm{\&phi;}\right)K_f}+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;\&mu;}}{\mathrm{\&mu;}}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}---\left(3\right)$

The Critical porosity model that Nur proposes, expression formula is shown below:

$\left\{\begin{array}{c}{K}_{\mathrm{dry}}=K_m(1-\frac{\mathrm{\&phi;}}{{\mathrm{\&phi;}}_c})\\ {\mathrm{\&mu;}}_{\mathrm{dry}}={\mathrm{\&mu;}}_m(1-\frac{\mathrm{\&phi;}}{{\mathrm{\&phi;}}_c})\end{array}\right.---\left(4\right)$

Wherein, φ _crepresent Critical porosity, K _dryrepresent the bulk modulus of dry rock, μ _dryrepresent the modulus of shearing of dry rock, K _mrepresent the bulk modulus of solid mineral matrix, μ _mrepresent the modulus of shearing of mineral substrate.

Launch further to obtain to formula (3) in conjunction with Nur formula (4):

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right](\frac{\mathrm{\&Delta;G}\left(\mathrm{\&phi;}\right)}{G\left(\mathrm{\&phi;}\right)}+\frac{\mathrm{\&Delta;}{K}_f}{K_f})+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}](\frac{\mathrm{\&Delta;}{\mathrm{\&mu;}}_m}{{\mathrm{\&mu;}}_m}+\frac{\mathrm{\&Delta;}({\mathrm{\&phi;}}_c-\mathrm{\&phi;})}{{\mathrm{\&phi;}}_c-\mathrm{\&phi;}})\\ +[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}\end{array}---\left(5\right)$

Will substitute into G (φ), launch further to obtain:

$\left.\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{\mathrm{\&Delta;}{K}_f}{K_f}[+\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;}{\mathrm{\&mu;}}_m}{{\mathrm{\&mu;}}_m}+[\frac{{\sec }^2\mathrm{\&theta;}}{4}-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{2{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}+\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;\&phi;}}{\mathrm{\&phi;}}\\ +[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;\&phi;}({\mathrm{\&phi;}}_c-\mathrm{\&phi;})}{\mathrm{\&phi;}({\mathrm{\&phi;}}_c-\mathrm{\&phi;})}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}\end{array}\right]---\left(6\right)$

Make f _m=φ μ, and utilize formula (4), the AVO approximate formula of the final sign fluid modulus built is as follows:

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{\mathrm{\&Delta;}{K}_f}{K_f}+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{4{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;}\left(f_m\right)}{f_m}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}\\ +(\frac{{\sec }^2\mathrm{\&theta;}}{4}-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{2{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}+\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;})\frac{\mathrm{\&Delta;\&phi;}}{\mathrm{\&phi;}}\end{array}---\left(7\right)$

Wherein, f _m=φ μ is the solid item of subsurface rock, and θ is incident angle, K _ffor the fluid modulus of subsurface rock, f _mfor the solid item of subsurface rock, φ is the factor of porosity of subsurface rock, and ρ is the density of subsurface rock, and μ is the modulus of shearing of subsurface rock, △ K _ffor the difference of the fluid modulus of both sides, interface, △ f _mfor the difference of both sides, interface solid item, △ ρ is the difference of the density of both sides, interface, and △ φ is the difference of the factor of porosity of both sides, interface, for dry rock P-S wave velocity ratio square, for saturated rock P-S wave velocity ratio square.

Wavelet extraction device 300, extracts wavelet for the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus.Figure 11 is the concrete structure block diagram of wavelet extraction device.

Fluid modulus data volume determining device 400, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Figure 12 is the concrete structure block diagram of fluid modulus data volume determining device.

Fluid type recognition device 500, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

The structured flowchart of the embodiment two of the system of a kind of fluid identification based on fluid modulus AVO inverting that Fig. 8 provides for the embodiment of the present invention, as shown in Figure 8, in embodiment two, this system specifically comprises:

Data collection device 100, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

Relative amplitude preserved processing device 600, for carrying out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road set information.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

Approximate formula construction device 200, for building the AVO approximate formula equation characterizing fluid modulus.

Wavelet extraction device 300, extracts wavelet for the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus.Figure 11 is the concrete structure block diagram of wavelet extraction device.

Fluid modulus data volume determining device 400, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Figure 12 is the concrete structure block diagram of fluid modulus data volume determining device.

Fluid type recognition device 500, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

The structured flowchart of the embodiment three of the system of a kind of fluid identification based on fluid modulus AVO inverting that Fig. 9 provides for the embodiment of the present invention, as shown in Figure 9, in embodiment three, this system specifically comprises:

Data collection device 100, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

Relative amplitude preserved processing device 600, for carrying out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road set information.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

Environmental correction device 700, for carrying out environmental correction to described well-log information;

Singular value cancellation element 800, for carrying out singular value elimination to the well-log information after environmental correction;

Speed is than determining device 900 in length and breadth, for determining dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of described object reservoir according to the well-log information after singular value is eliminated.In concrete embodiment, full wave train log is carried out in exploration work area, the well-log information obtained, as prior imformation, needs, after the pre-service such as environmental correction, singular value elimination, to calculate dry rock P-S wave velocity ratio γ in conjunction with rock physics experimental formula or experiment statistics result _dry, saturated rock P-S wave velocity ratio γ _satnumerical value.

Modulus of shearing curve determining device 1000, for determining the fluid modulus curve corresponding with described well-log information and modulus of shearing curve according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.In a particular embodiment, fluid modulus is K _f, modulus of shearing is μ curve.

Approximate formula construction device 200, for building the AVO approximate formula equation characterizing fluid modulus.

Wavelet extraction device 300, extracts wavelet for the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus.Figure 11 is the concrete structure block diagram of wavelet extraction device.

Fluid modulus data volume determining device 400, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume, Figure 12 is the concrete structure block diagram of fluid modulus data volume determining device.

Fluid type recognition device 500, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

The structured flowchart of the embodiment four of the system of a kind of fluid identification based on fluid modulus AVO inverting that Figure 10 provides for the embodiment of the present invention, as shown in Figure 10, in embodiment four, this system specifically comprises:

Data collection device 100, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data.

The collection of Prestack seismic data is in a particular embodiment by such as under type: in exploration work area, according to the degree of depth and the geology characteristic of zone of interest, considering the stereo observing systems because usually designing wide-azimuth such as NMO stretching, interference wave, multiple reflection, ensuring enough offset distances, position angle.Through exciting, receiving, obtain meeting the Prestack seismic data that AVO analyzes the wide-azimuth wide-angle of demand.

The collection of well-log information is in a particular embodiment by such as under type: in exploration work area, carry out full wave train log, obtain well-log information, mainly comprise the full wave train log curves such as velocity of longitudinal wave, shear wave velocity, density, the interpretation results curves such as factor of porosity, well logging layer position, log data etc.

Relative amplitude preserved processing device 600, for carrying out relative amplitude preserved processing to described Prestack seismic data, obtains CMP road set information.

Relative amplitude preserved processing is carried out to described Prestack seismic data, to ensure to be formed the high-quality CMP road set information that can be used for carrying out AVO inverting.Concrete relative amplitude preserved processing comprises: the correction, inverse Q filtering, surface consistent processing, Multiple attenuation, pre-stack noise suppress etc. of wavefront diffusion compensation, source pattern and receiver pattern effect.

Environmental correction device 700, for carrying out environmental correction to described well-log information;

Singular value cancellation element 800, for carrying out singular value elimination to the well-log information after environmental correction;

Speed is than determining device 900 in length and breadth, for determining dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of described object reservoir according to the well-log information after singular value is eliminated.In concrete embodiment, full wave train log is carried out in exploration work area, the well-log information obtained, as prior imformation, needs, after the pre-service such as environmental correction, singular value elimination, to calculate dry rock P-S wave velocity ratio γ in conjunction with rock physics experimental formula or experiment statistics result _dry, saturated rock P-S wave velocity ratio γ _satnumerical value.

Modulus of shearing curve determining device 1000, for determining the fluid modulus curve corresponding with described well-log information and modulus of shearing curve according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.In a particular embodiment, fluid modulus is K _f, modulus of shearing is μ curve.

Tracing of horizons device 1100, for carrying out meticulous tracing of horizons according to described Prestack seismic data, well-log information, Geological Achievements data to object reservoir, obtains seismic horizon data.

In a particular embodiment, in conjunction with the geologic background in work area, meet on the basis of work area geologic sedimentation pattern and Sequence Stratigraphic Formation in guarantee zone of interest position, fine geology explanation is carried out to the zone of interest of research, dark relation when explaining that the seismic horizon data obtained not only is used for identifying, also for setting up the model constrained of refutation process.

Approximate formula construction device 200, for building the AVO approximate formula equation characterizing fluid modulus.

Wavelet extraction device 300, extracts wavelet for the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus.Figure 11 is the concrete structure block diagram of wavelet extraction device 300.As shown in Figure 11, this wavelet extraction device specifically comprises:

Factor of porosity extraction module 301, for extracting density and the factor of porosity of subsurface rock from described well-log information.In a particular embodiment, the density of subsurface rock is represented by ρ, and the factor of porosity of subsurface rock is represented by φ.

Solid item determination module 302, for the solid item according to described modulus of shearing curve and described factor of porosity determination subsurface rock, in a particular embodiment, the solid item of subsurface rock passes through f _mrepresent, then f _m=φ μ.

Wavelet extraction module 303, extracts wavelet for the density according to described subsurface rock, solid item, factor of porosity, fluid modulus curve, the AVO approximate formula characterizing fluid modulus, prestack CMP road collection and seismic horizon data.

As shown in Figure 4, in embodiment four, this system also comprises:

Fluid modulus data volume determining device 400, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume.Figure 12 is the concrete structure block diagram of fluid modulus data volume determining device.As shown in Figure 12, fluid modulus data volume determining device specifically comprises:

Inversion objective function sets up module 401, for utilizing described prestack CMP road collection, well-log information, Geological Achievements data and wavelet, based on bayesian theory, use gauss of distribution function is likelihood function, Cauchy is distributed as and prior-constrainedly sets up AVO inversion objective function.The AVO inversion objective function set up is:

(G ^ΤG+ηQ+αC ^ΤC)m＝G ^Τd+αC ^Τξ (8)

$\mathrm{\&eta;}=\mathrm{\&lambda;}\frac{{\mathrm{\&sigma;}}_n^2}{{\mathrm{\&sigma;}}_m^2}$

$\mathrm{\&xi;}=\frac{1}{2}\ln \left(\frac{M}{M_0}\right)$

Wherein, for the variance of noise in CMP road set information, for the variance of elastic parameter relative variation, λ, α are weighting coefficient, and m is the elastic parameter relative variation matrix treating inverting, and G is for just to calculate submatrix, and C is integration matrix, and d is CMP road collection matrix, and Q is diagonally opposing corner weighting matrix, and M is model constrained matrix, M ₀for the average of M.

Relative variation determination module 402, for utilizing heavy weighted least-squares iterative algorithm to solve described AVO inversion objective function, obtains the relative variation of fluid modulus.In a particular embodiment, this step specifically comprises:

(1) initial reflection coefficient sequence (initial model) m, is set up ₀;

(2), according to the quality of seismic data, suitable weighting coefficient λ, α is selected;

(3), G is calculated according to prior imformation, model data and log data ^tg, G ^Τd, C ^Τc, C ^Τξ, utilizes the inversion result m of kth-1 iteration _k-1(iteration utilizes initial model m for the first time ₀) calculate η and Q;

(4), to formula (8) carry out inversion calculation, obtain kth time inversion result:

m _k＝(G ^ΤG+ηQ+αC ^ΤC) ^-1(G ^Τd+αC ^Τξ)

In other embodiments of the present invention, in addition to the foregoing steps, the following condition of convergence can also be designed:

$\frac{|J\left(m_k\right)-J\left(m_{k-1}\right)|}{\left(\right|J\left(m_k\right)|+|J\left(m_{k-1}\right)\left|\right)/2}<e$

_efor convergence error.Utilize m _kcalculate target function value J (m _k), the termination of iterations when meeting the above-mentioned condition of convergence, when not meeting the condition of convergence, rebound (2) step, iteration proceeds.

Conversion module 403, is converted into fluid modulus data volume for utilizing trace integral thought by described relative variation.

As shown in Figure 10, in embodiment four, this system also comprises:

Fluid type recognition device 500, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

After estimation obtains fluid modulus data volume, contrast with the theoretical value of reservoir fluid bulk modulus, namely can identify the type of fluid in reservoir pore space.

As mentioned above, be the system of a kind of fluid identification based on fluid modulus AVO inverting provided by the invention, achieve the fluid modulus parameter estimation being separated AVO approximate formula based on fluid modulus, fluid modulus parameter is high containing fluid type susceptibility to reservoir, and eliminate the fluid identification illusion that the solid effects such as reservoir rock factor of porosity cause to greatest extent, improve reservoir pore space fluid type forecasting reliability.

Below in conjunction with specific embodiment, introduce technical scheme of the present invention in detail.

Figure 13 is pore fluid type is in the gentle situation of water, velocity of longitudinal wave is with the changing trend diagram of factor of porosity and water saturation, Figure 14 is pore fluid type is in the gentle situation of water, Gassmann fluid item is with the changing trend diagram of factor of porosity and water saturation, Figure 15 is pore fluid type is in the gentle situation of water, and fluid modulus is with the changing trend diagram of factor of porosity and water saturation.In order to Study of Fluid instruction susceptibility, adopt fluid alternative method to devise three kinds of models, be namely conventionally used for the Rock Elastic Parameters velocity of longitudinal wave V of instruction fluid type _p, Gassmann fluid item f and fluid modulus K _fwith the variation model of pore fluid type and factor of porosity.As we can see from the figure, be compared to pore fluid type, factor of porosity is to common elastic parameter V _pimpact is large, and f takes second place, K _fvalue to place one's entire reliance upon fluid type of reservoir through, the illusion that the solid effect (particularly factor of porosity) that can there is reservoir rock when namely utilizing common elastic parameter to carry out fluid identification in actual applications causes, and K _fbecome complete linear trends of change with water saturation, fluid identification can be participated in as a kind of more responsive elastic parameter.

Figure 16 is layer model curve synoptic diagram one-dimensionally, is used for verifying feasibility and the noise immunity of inversion method.Convolution 40Hz zero phase Ricker wavelet generates prestack CMP road collection (incident angle range is 0-30 degree, and time sampling interval is 2ms), analyzes based on this to the inversion result under different signal to noise ratio (S/N ratio) condition.

Prestack CMP road collection schematic diagram when Figure 17 is non-plus noise, Figure 18 is the inversion result schematic diagram that prestack CMP road collection when utilizing non-plus noise carries out inverting and obtains.Wherein solid line represents realistic model, and dotted line represents inversion result.By comparing discovery, when noiselessness, under the constraint of prior imformation, fluid modulus K _finversion result and model data coincide better.

The prestack CMP road collection schematic diagram of Figure 19 to be signal to noise ratio (S/N ratio) be 1:1, Figure 20 is the inversion result schematic diagram that the prestack CMP road collection utilizing signal to noise ratio (S/N ratio) to be 1:1 carries out inverting and obtains.Wherein solid line represents realistic model, and dotted line represents inversion result.When signal to noise ratio (S/N ratio) is 1:1, the fluid modulus K of inverting _falthough be subject to certain impact, general trend is still close to realistic model, and error is in tolerance interval.Therefore known by model measurement, the fluid modulus extracting method originally researched and proposed is adopted to have good compacting to noise under the constraint of well logging prior imformation, the quantitative extraction of fluid modulus parameter can be realized preferably, for fluid identification provides reliable elastic parameter data supporting.

Figure 21 is the superposition seismic section schematic diagram of research survey line.In figure to throw curve be well logging interpretation histogram, triangle represents gas-bearing formation, and rhombus represents water layer.Two cover sandstone are grown near its 2.58s and 2.64s, well-log information display 2.58s place Sandstone Gas Bearing, and 2.64s place sandstone is moisture, but owing to affecting by palaeotopography, under cover water bearing sand factor of porosity higher than the factor of porosity above covering gas sand, easily cause containing Fluid Anomalies illusion in fluid identification.

Figure 22 is the fluid modulus K of estimation _fdiagrammatic cross-section.Can see that itself and result of log interpretation are coincide better, reflect that well surrounding formation is containing characteristic of fluid and distribution situation, demonstrates the validity of fluid modulus parameter in fluid identification comparatively accurately.

In sum, the method and system of a kind of fluid identification based on fluid modulus AVO inverting that the present invention proposes, in order to improve the stability of fluid modulus estimation, this programme sets up inversion objective function based on bayesian theory, utilize heavy weighted least-squares iterative algorithm loop iteration to solve objective function, realize the quantitative estimation of earthquake scale fluid modulus.In specific implementation process, first need the pre-service carrying out prestack CMP road set information and well-log information, then carry out wavelet extraction, the basis realizing the extraction of fluid modulus relative variation finally obtains fluid modulus parameter.

Rock Elastic Parameters based on conventional AVO approximate estimation easily produces reservoir by solid-liquid coupling properties influence and sentences knowledge illusion containing fluid, the present invention is based on poroelasticity MEDIUM THEORY and Critical porosity model, fluid modulus parameters separated is realized in reflection coefficient is approximate, fluid modulus is more responsive to reservoir fluid information, utilize the AVO approximate formula characterizing fluid modulus to carry out AVO inverting and can estimate fluid modulus parameter, avoid fluid identification illusion, improve reservoir pore space fluid type forecasting reliability.

One of ordinary skill in the art will appreciate that all or part of flow process realized in above-described embodiment method, the hardware that can carry out instruction relevant by computer program has come, described program can be stored in general computer read/write memory medium, this program, when performing, can comprise the flow process of the embodiment as above-mentioned each side method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-Only Memory, ROM) or random store-memory body (Random AccessMemory, RAM) etc.

Those skilled in the art can also recognize that the various functions that the embodiment of the present invention is listed are the designing requirements realizing depending on specific application and whole system by hardware or software.Those skilled in the art for often kind of specifically application, can use the function described in the realization of various method, but this realization can should not be understood to the scope exceeding embodiment of the present invention protection.

Apply specific embodiment in the present invention to set forth principle of the present invention and embodiment, the explanation of above embodiment just understands method of the present invention and core concept thereof for helping; Meanwhile, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.

Claims (16)

1. based on a method for the fluid identification of fluid modulus AVO inverting, it is characterized in that, described method specifically comprises:

Gather the Prestack seismic data of object reservoir, well-log information and Geological Achievements data;

Build the change AVO approximate formula of the amplitude offset distance characterizing fluid modulus;

AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus extracts wavelet;

According to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume;

According to the type of fluid in the described current reservoir pore space of fluid modulus data volume identification.

2. method according to claim 1, is characterized in that, described method also comprised before building the AVO approximate formula characterizing fluid modulus:

Relative amplitude preserved processing is carried out to described Prestack seismic data, obtains common midpoint CMP road set information.

3. method according to claim 2, is characterized in that, described method also comprised before building the AVO approximate formula characterizing fluid modulus:

Environmental correction is carried out to described well-log information;

Singular value elimination is carried out to the well-log information after environmental correction;

Dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of described object reservoir is determined according to the well-log information after singular value is eliminated;

The fluid modulus curve corresponding with described well-log information and modulus of shearing curve is determined according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.

4. method according to claim 3, is characterized in that, described method also comprised before building the AVO approximate formula characterizing fluid modulus:

According to described Prestack seismic data, well-log information, Geological Achievements data, meticulous tracing of horizons is carried out to object reservoir, obtain seismic horizon data.

5. method according to claim 4, is characterized in that, the AVO approximate formula of described sign fluid modulus is:

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{{\mathrm{\&Delta;K}}_f}{K_f}+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{4\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;}\left(f_m\right)}{f_m}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}\\ +(\frac{{\sec }^2\mathrm{\&theta;}}{4}-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{2\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}+\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;})\frac{\mathrm{\&Delta;\&phi;}}{\mathrm{\&phi;}}\end{array}$

Wherein, f _m=φ μ is the solid item of subsurface rock, and θ is incident angle, K _ffor the fluid modulus of subsurface rock, f _mfor the solid item of subsurface rock, φ is the factor of porosity of subsurface rock, and ρ is the density of subsurface rock, and μ is the modulus of shearing of subsurface rock, △ K _ffor the difference of the fluid modulus of both sides, interface, △ f _mfor the difference of both sides, interface solid item, △ ρ is the difference of the density of both sides, interface, and △ φ is the difference of the factor of porosity of both sides, interface, for dry rock P-S wave velocity ratio square, for saturated rock P-S wave velocity ratio square.

6. method according to claim 5, is characterized in that, extracts wavelet specifically comprise according to the AVO approximate formula of described Prestack seismic data, well-log information, Geological Achievements data and sign fluid modulus:

Density and the factor of porosity of subsurface rock is extracted from described well-log information;

According to the solid item of described modulus of shearing curve and described factor of porosity determination subsurface rock;

Wavelet is extracted according to the density of described subsurface rock, solid item, factor of porosity, fluid modulus curve, the AVO approximate formula characterizing fluid modulus, prestack CMP road collection and seismic horizon data.

7. method according to claim 6, is characterized in that, specifically comprises according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume:

Prestack CMP road collection, well-log information, Geological Achievements data and wavelet described in utilization, based on bayesian theory, use gauss of distribution function is likelihood function, Cauchy is distributed as and prior-constrainedly sets up AVO inversion objective function;

Utilize heavy weighted least-squares iterative algorithm to solve described AVO inversion objective function, obtain the relative variation of fluid modulus;

Utilize trace integral thought that described relative variation is converted into fluid modulus data volume.

8. method according to claim 7, is characterized in that, the AVO inversion objective function of foundation is:

(G ^ΤG+ηQ+αC ^ΤC)m＝G ^Τd+αC ^Τξ

$\mathrm{\&eta;}=\mathrm{\&lambda;}\frac{{\mathrm{\&sigma;}}_n^2}{{\mathrm{\&sigma;}}_m^2}$

$\mathrm{\&xi;}=\frac{1}{2}\ln \left(\frac{M}{M_0}\right)$

Wherein, for the variance of noise in CMP road set information, for the variance of elastic parameter relative variation, λ, α are weighting coefficient, and m is the elastic parameter relative variation matrix treating inverting, and G is for just to calculate submatrix, and C is integration matrix, and d is CMP road collection matrix, and Q is diagonally opposing corner weighting matrix, and M is model constrained matrix, M ₀for the average of M.

9. based on a system for the fluid identification of fluid modulus AVO inverting, it is characterized in that, described system specifically comprises:

Data collection device, for gathering the Prestack seismic data of object reservoir, well-log information and Geological Achievements data;

Approximate formula construction device, for building the change AVO approximate formula of the amplitude offset distance characterizing fluid modulus;

Wavelet extraction device, extracts wavelet for the AVO approximate formula according to described Prestack seismic data, well-log information, Geological Achievements data and described sign fluid modulus;

Fluid modulus data volume determining device, for according to described Prestack seismic data, well-log information, Geological Achievements data and wavelet determination fluid modulus data volume;

Fluid type recognition device, for the type according to fluid in the described current reservoir pore space of fluid modulus data volume identification.

10. system according to claim 9, is characterized in that, described system also comprises:

Relative amplitude preserved processing device, for carrying out relative amplitude preserved processing to described Prestack seismic data, obtains common midpoint CMP road set information.

11. systems according to claim 10, is characterized in that, described system also comprises:

Environmental correction device, for carrying out environmental correction to described well-log information;

Singular value cancellation element, for carrying out singular value elimination to the well-log information after environmental correction;

Velocity ratio determining device in length and breadth, for determining dry rock P-S wave velocity ratio, the saturated rock P-S wave velocity ratio of described object reservoir according to the well-log information after singular value is eliminated;

Modulus of shearing curve determining device, for determining the fluid modulus curve corresponding with described well-log information and modulus of shearing curve according to the dry core sample P-S wave velocity ratio of described object reservoir and described well-log information.

12. systems according to claim 11, is characterized in that, described system also comprises:

Tracing of horizons device, for carrying out meticulous tracing of horizons according to described Prestack seismic data, well-log information, Geological Achievements data to object reservoir, obtains seismic horizon data.

13. systems according to claim 12, is characterized in that, the AVO approximate formula of described sign fluid modulus is:

$\begin{array}{c}{R}_{\mathrm{PP}}\left(\mathrm{\&theta;}\right)=\left[(1-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2})\frac{{\sec }^2\mathrm{\&theta;}}{4}\right]\frac{{\mathrm{\&Delta;K}}_f}{K_f}+[\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{4\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}-\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;}]\frac{\mathrm{\&Delta;}\left(f_m\right)}{f_m}+[\frac{1}{2}-\frac{{\sec }^2\mathrm{\&theta;}}{4}]\frac{\mathrm{\&Delta;\&rho;}}{\mathrm{\&rho;}}\\ +(\frac{{\sec }^2\mathrm{\&theta;}}{4}-\frac{{\mathrm{\&gamma;}}_{\mathrm{dry}}^2}{{2\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sec }^2\mathrm{\&theta;}+\frac{2}{{\mathrm{\&gamma;}}_{\mathrm{sat}}^2}{\sin }^2\mathrm{\&theta;})\frac{\mathrm{\&Delta;\&phi;}}{\mathrm{\&phi;}}\end{array}$

Wherein, f _m=φ μ is the solid item of subsurface rock, and θ is incident angle, K _ffor the fluid modulus of subsurface rock, f _mfor the solid item of subsurface rock, φ is the factor of porosity of subsurface rock, and ρ is the density of subsurface rock, and μ is the modulus of shearing of subsurface rock, △ K _ffor the difference of the fluid modulus of both sides, interface, △ f _mfor the difference of both sides, interface solid item, △ ρ is the difference of the density of both sides, interface, and △ φ is the difference of the factor of porosity of both sides, interface, for dry rock P-S wave velocity ratio square, for saturated rock P-S wave velocity ratio square.

14. systems according to claim 13, is characterized in that, described wavelet extraction device specifically comprises:

Factor of porosity extraction module, for extracting density and the factor of porosity of subsurface rock from described well-log information;

Solid item determination module, for the solid item according to described modulus of shearing curve and described factor of porosity determination subsurface rock;

Wavelet extraction module, extracts wavelet for the density according to described subsurface rock, solid item, factor of porosity, fluid modulus curve, the AVO approximate formula characterizing fluid modulus, prestack CMP road collection and seismic horizon data.

15. systems according to claim 14, is characterized in that, described fluid modulus data volume determining device specifically comprises:

Inversion objective function sets up module, for utilizing described prestack CMP road collection, well-log information, Geological Achievements data and wavelet, based on bayesian theory, use gauss of distribution function is likelihood function, Cauchy is distributed as and prior-constrainedly sets up AVO inversion objective function;

Relative variation determination module, for utilizing heavy weighted least-squares iterative algorithm to solve described AVO inversion objective function, obtains the relative variation of fluid modulus;

Conversion module, is converted into fluid modulus data volume for utilizing trace integral thought by described relative variation.

16. systems according to claim 15, is characterized in that, the AVO inversion objective function of foundation is:

(G ^ΤG+ηQ+αC ^ΤC)m＝G ^Τd+αC ^Τξ

$\mathrm{\&eta;}=\mathrm{\&lambda;}\frac{{\mathrm{\&sigma;}}_n^2}{{\mathrm{\&sigma;}}_m^2}$

$\mathrm{\&xi;}=\frac{1}{2}\ln \left(\frac{M}{M_0}\right)$

Wherein, for the variance of noise in CMP road set information, for the variance of elastic parameter relative variation, λ, α are weighting coefficient, and m is the elastic parameter relative variation matrix treating inverting, and G is for just to calculate submatrix, and C is integration matrix, and d is CMP road collection matrix, and Q is diagonally opposing corner weighting matrix, and M is model constrained matrix, M ₀for the average of M.