3D in-situ characterization method for heterogeneity in generating and reserving performances of shale

Patent metadata

Field	Value
Publication number	US-11834947-B2
Application number	US-202117489496-A
Country	US
Kind code	B2
Filing date	Sep 29, 2021
Priority date	Dec 1, 2020
Publication date	Dec 5, 2023
Grant date	Dec 5, 2023

Abstract

The present invention discloses a three-dimensional in-situ characterization method for heterogeneity in generating and reserving performances of shale. The method includes the following steps: establishing a logging in-situ interpretation model of generating and reserving parameters based on lithofacies-lithofacies-well coupling, and completing single-well interpretation; establishing a 3D seismic in-situ interpretation model of generating and reserving parameters by using well-seismic coupling; establishing a spatial in-situ framework of a layer group based on lithofacies-well-seismic coupling, and establishing a spatial distribution trend framework of small layers of a shale formation by using 3D visualized comparison of a vertical well; and implementing 3D in-situ accurate characterization of shale generating and reserving performance parameters by using lithofacies-well-seismic coupling based on the establishment of the seismic-lithofacies dual-control parameter field. The present invention integrates an in-situ technology into shale logging, seismic generating and reserving parameter interpretation, and the establishment of a 3D mesh model of small layers of shale, which realizes the accurate description of the heterogeneity in TOC content and porosity value of shale oil and gas in a 3D space, and provides a reliable technical support for shale oil and gas exploration and development.

First claim

The invention claimed is:

1. A three-dimensional in-situ characterization method for heterogeneity in generating and reserving performances of shale, to overcome the technical problem that most of the total organic carbon (TOC) content and porosity value logging interpretation in the prior art is directly derived from the matching of core data and logging data, lack of big data mining process between core data and logging data, which leads to a large error between the logging interpretation results and the actual TOC content and porosity values of shale layer, and with the purpose of achieving accurate characterization of the heterogeneity of TOC content and porosity values of shale oil gas in 3D space and providing reliable technical support for shale oil exploration and development, comprising the following steps:
S1: establishing a logging in-situ interpretation model of generating and reserving parameters based on lithofacies-lithofacies-well coupling, and completing point-by-point interpretation of generating and reserving parameters of a single well, wherein the S1 specifically comprises the following sub-steps:
S101: returning the TOC and porosity value obtained by a core test to an in-situ drilling depth by core location, extracting curve values of conventional logging series at the same depth, mining a relationship between the TOC and the conventional logging series and a relationship between the porosity and the conventional logging series by using a classification regression tree algorithm, and determining a sensitive logging curve for the TOC and the porosity;
S102: establishing a TOC and porosity calculation model for the sensitive logging curve by using a multiple regression method, and completing single-well point-by-point calculation of the TOC and the porosity; counting the TOC and the porosity value of each type of shale lithofacies by using a shale lithofacies mode established on the basis of core descriptions; extracting the statistics of the TOC and porosity value of each type of shale lithofacies, establishing a TOC and porosity calculation model by merging the statistics, and forming a logging interpretation model for generating and reserving performance parameters of shale; and
S103: based on the statistics of the TOC and porosity value of each type of shale lithofacies, correcting and perfecting single-well point-by-point calculation results of the TOC and porosity value on the basis of single-well lithofacies analysis results, to complete the single-well point-by-point interpretation of the TOC and porosity value;
S2: establishing an optimal well-seismic coupling interpretation model that characterizes the TOC content and porosity of a shale formation based on well-seismic coupling;
S3: completing the establishment of a structural distribution model of top and bottom surfaces of a layer group based on lithofacies-electrical facies of vertical well-seismic coupling, thereby forming an in-situ spatial framework of the layer group;
S4: establishing a structural distribution model of top and bottom surfaces of small layers based on a vertical well by using 3D visualization comparison of the vertical well, thereby forming a spatial distribution trend framework of small layers of the shale formation;
S5: establishing a structural distribution model of top and bottom surfaces of small layers based on vertical well+horizontal well by using 3D visualization comparison of the horizontal well, thereby forming an in-situ three-dimensional mesh model of the small layers of the shale formation;
S6: establishing a three-dimensional model and a lithofacies model of seismic attributes of in-situ TOC content and porosity of the shale formation, thereby forming a three-dimensional visualized seismic-lithofacies dual-control parameter field of generating and reserving performance parameters of shale; and
S7: coarsening single-well point-by-point data of the TOC content and porosity completed on the basis of lithofacies-lithofacies-well coupling into an in-situ three-dimensional mesh model of the small layers of shale, to form a main input of three-dimensional visualization modeling; coupling the seismic-lithofacies dual-control parameter field to the logging TOC and porosity by taking TOC and porosity statistics of various lithofacies in a three-dimensional space of a lithofacies model as constraints, taking a three-dimensional model of seismic attributes of the TOC content and porosity as a changing trend, and using a simulation method of combining sequential Gaussian with co-kriging, thereby realizing the three-dimensional in-situ characterization of the spatial heterogeneity characteristics of the TOC content and porosity of shale.

2. The three-dimensional in-situ characterization method for heterogeneity in generating and reserving performances of shale according to claim 1 , wherein the sensitive logging curves for the TOC and porosity include a natural gamma GR logging curve, a sonic time difference AC logging curve, a compensated neutron CNL logging curve, a compensated density DEN logging curve and a deep lateral resistivity RT logging curve.

3. The three-dimensional in-situ characterization method for heterogeneity in generating and reserving performances of shale according to claim 1 , wherein the S2 specifically comprises the following sub-steps:
S201: extracting 3D seismic body attributes from modeling software;
S202: preliminarily screening seismic body attribute types that can be used to express the TOC content and porosity of a shale formation according to an original geological meaning of seismic body attributes, judging the independence of the screened seismic body attributes by using a R-type factor analysis method, and eliminating the seismic body attributes with high correlation to obtain preferred seismic body attributes that express the TOC content and porosity value of the shale formation; and
S203: establishing an optimal well-seismic coupling interpretation model that characterizes the TOC content and porosity of the shale formation by using well-seismic coupling and adopting a single attribute linear regression method, a multi-attribute nested combination analysis method and a self-feedback neural network method respectively.

4. The three-dimensional in-situ characterization method for heterogeneity in generating and reserving performances of shale according to claim 1 , wherein the S3 specifically comprises the following sub-steps:
S301: establishing an in-situ layering model of lithofacies-electrical facies coupling for top and bottom surfaces of a layer group and an interface of each small layer in the layer group based on lithofacies characteristics of a vertical well under exploration evaluation, and characteristics of a lithology indicator curve, a porosity indicator curve, or an oil-gas-bearing indicator curve, to form an in-situ spatial framework of the top and bottom surfaces of the layer group and interfaces of the small layers in the layer group at the location of a drilling well point;
S302: establishing a time-depth conversion relationship by using a synthetic recording method, and projecting in-situ depth information of the top and bottom surfaces of the layer group identified by the vertical well under exploration evaluation onto a seismic-time profile to form a well-seismic coupling relationship of top and bottom interfaces of a main oil-producing layer group of the shale formation; and
S303: converting time data of the top and bottom surfaces of the layer group into depth data by using the established time-depth conversion relationship; completing the establishment of a structural distribution model of the top and bottom surfaces of the layer group under the condition of ensuring that a residual at the vertical well point under exploration evaluation is zero by means of a multiple mesh approx

Assignees

• Univ Southwest Petroleum

Inventors

• Ou Chenghua
• Li Chaochun

Classifications

• E21B49/005 Primary

  Testing the nature of borehole walls or the formation by using drilling mud or cutting data · CPC title

• E21B43/30

  Specific pattern of wells, e.g. optimising the spacing of wells · CPC title

• E21B49/087

  Well testing, e.g. testing for reservoir productivity or formation parameters · CPC title

• E21B2200/20

  Computer models or simulations, e.g. for reservoirs under production, drill bits · CPC title

• G01V1/345 Primary

  Visualisation of seismic data or attributes, e.g. in 3D cubes · CPC title