Seismic rock physics inversion method based on large area tight reservoir

Patent metadata

Field	Value
Publication number	US-10983232-B2
Application number	US-201716317822-A
Country	US
Kind code	B2
Filing date	Jul 11, 2017
Priority date	Jul 15, 2016
Publication date	Apr 20, 2021
Grant date	Apr 20, 2021

Abstract

A seismic rock physics inversion method based on a large area tight reservoir includes steps: building a multi-scale 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 single-well rock physics template, preferably a standard template; considering lateral variations and heterogeneity of reservoir geological features, fine-tuning 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 three-dimensional work area rock physics template data volume, and combining the data volume with pre-stack 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.

First claim

What is claimed is:

1. A seismic rock physics inversion method based on a large area tight reservoir, wherein comprising the following specific steps:
step 101 : predicting, by a processor, a wave response dispersion based on a poroelasticity theory, building, by the processor, a multi-scale rock physics model, to associate with multi-scale data, wherein the building the multi-scale rock physics model, by the processor, 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 gas-water patchy saturation;
step 102 : analyzing and correcting, by the processor, a logging interpretation result based on a model and gas testing situations of reference wells obtained by sensors, analyzing, by the processor, 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 P-wave velocity Vp, a S-wave velocity Vs, a P-wave impedance Zp, a S-wave impedance Zs, a P-wave velocity-to-S-wave velocity ratio Vp/Vs, a Lamé constant λ, a shear modulus μ, a product λρ of a Lamé constant and a density, a product λμ of a Lamé constant and a shear modulus, a quasi pressure PR, a product μρ of a shear modulus and a density; and the analyzing fluid sensitivity comprises: measuring the P-wave velocity Vp and the S-wave velocity Vs in the scale of ultrasonic wave and a wave velocity during variation of saturations of gas and water, that is, a cross-plot of Vp/Vs and a wave impedance;
step 103 : preferably selecting, by the processor, each single-well template to manufacture a work area standard template as a single-well rock physics template built based on each piece of reference well data obtained by the sensors, wherein the work area standard template preferably uses the product λρ of the Lamé constant and the density as a vertical coordinate and the P-wave impedance as a horizontal coordinate;
step 104 : fine-tuning, by the processor, 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, by the processor, the whole work area, building, by the processor, a three-dimensional work area rock physics template data volume, and combining, by the processor, the three-dimensional work area rock physics template data volume with seismic pre-stack inversion to calculate a porosity and a saturation of a target layer; performing, by the processor, large-area three-dimensional rock physics template parameter inversion in the whole work area, smoothing, by the processor, an inversion result, and finally, outputting, by the processor, a reservoir parameter inversion data volume to a display, thereby implementing quantitative interpretation on the porosity and the saturation of the reservoir; and the building the three-dimensional work area rock physics template data volume is cutting and sorting a to-be-inverted and interpreted three-dimensional seismic data volume according to project requirements, performing pre-stack three-dimensional seismic inversion, and performing inverse calculation on the porosity and the saturation of the reservoir; and
step 105 : predicting, by the processor, an amount of hydrocarbon of the reservoir based on the porosity and the saturation of the reservoir calculated in step 104 to determine gas enriched areas of the reservoir.

2. The seismic rock physics inversion method based on a large area tight reservoir according to claim 1 , wherein modeling of the building the multi-scale rock physics model, by the processor, in step 101 comprises: calculating, by the processor, an elastic modulus of a rock matrix and an elastic modulus of a rock skeleton, and obtaining, by the processor, an effective elastic modulus of the rock matrix by using a Voigt-Reuss-Hill average equation:

M
VRH

=

1
2

⁢

(

∑

i
=
1

N

⁢

f
i

⁢

M
i

+

1

∑

i
=
1

N

⁢

f
i

M
i

)

,

(
1
)

wherein 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:
(1− y ) d/dy [ K *( y )]=( K 2 −K *( y )) P ( * 2) ( y )  (2a)

(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 of a primary-phase material (a phase 1) of an initial principal mineral phase, K 2 and μ 2 are a bulk modulus and a

Assignees

• Univ Hohai

Inventors

• Ba Jing
• Tan Wenhui
• Qian Wei
• Cheng Wei

Classifications

• G01V1/306 Primary

  for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles · CPC title

• G01V1/282 Primary

  Application of seismic models, synthetic seismograms · CPC title

• G01V2210/6169

  using well-logging · CPC title