Fracture interpretation with resistivity and sonic logs in biaxial anisotropic formations

US11230922B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11230922-B2
Application numberUS-201615777751-A
CountryUS
Kind codeB2
Filing dateJan 20, 2016
Priority dateJan 20, 2016
Publication dateJan 25, 2022
Grant dateJan 25, 2022

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Abstract

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Evaluation of formation and fracture characteristics based on multicomponent induction (MCI) and multipole sonic logging (MSL) data includes automated calculation of inverted biaxial anisotropy (BA) parameters for the formation by performing an iterative BA inversion operation based on the MCI log data and using a BA formation model that accounts for transfers by axial formation anisotropy to resistivity. The inverted BA parameters and the processed MSL data can be used, in combination, to calculate a quantified value for an identification function, to indicate estimated presence or absence of a fracture in the formation.

First claim

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What is claimed is: 1. A method comprising: accessing multicomponent induction (MCI) and multipole sonic logging (MSL) data captured by measurement tools in a borehole extending through a subsurface formation; calculating, using one or more computer processors, inverted biaxial anisotropy (BA) parameters by performing an iterative inversion operation on the MCI data; performing fracture analysis, using one or more computer processors, to identify one or more fracture properties of the subsurface formation based at least in part on the MSL data and one or more of the inverted BA parameters; operating a controlled device based at least in part on the fracture analysis, wherein performing the fracture analysis further comprises identifying presence of a fracture in the formation by calculating a value of an identification function based on formation parameters calculated from the MCI and MSL data; wherein the identification function is variable as a function of the inverted BA parameters, an inverted TI parameter, and a parameter from the MSL data; determining if the value of the identification function meets a threshold value; and based upon the determination, identifying the presence of a fracture in the formation. 2. The method of claim 1 , further comprising: calculating, using one or more computer processors, inverted transverse isotropy (TI) parameters by performing an iterative inversion operation on the MCI data. 3. The method of claim 2 , wherein the iterative inversion operation is performed on the MCI data using a TI formation model that represents simulated formation resistivity characteristics that account for transverse formation isotropy to resistivity. 4. The method of claim 1 , wherein the iterative inversion operation on the MCI data uses a BA formation model that represents simulated formation resistivity characteristics that account for transverse biaxial formation anisotropy to resistivity. 5. The method of claim 1 , wherein performing fracture analysis further comprises estimating a fracture geometric parameter using a fracture formation model that represents formation resistivity characteristics in a homogeneous unbounded formation. 6. The method of claim 1 , wherein the performing of the BA inversion operation is based on single-frequency MCI measurement data. 7. The method of claim 1 , wherein the controlled device comprises a display device to display one or more fracture characteristics based at least in part on the fracture analysis. 8. The method of claim 1 , further comprising: calculating, using one or more processors, a fracture strike or an azimuth angle based on both the MCI and MSL data. 9. The method of claim 1 , further comprising: calculating, using one or more processors, borehole corrected measurement data by processing the MCI data to correct for borehole effects. 10. The method of claim 9 , further comprising: applying a dip-effect correction to borehole corrected measurement data. 11. The method of claim 1 , wherein calculating of the inverted BA parameters is based on raw MCI data, and further wherein the calculating of the inverted BA parameters comprises performing a set of processing operations that comprises at least the BA inversion operation, the set of processing operations excluding any non-inversion operation to correct for borehole effects using multi-frequency MCI measurement data. 12. A system comprising: a data access module to access multicomponent induction (MCI) and multipole sonic logging (MSL) data captured by measurement tools in a borehole extending through a subsurface formation; and an inversion module that comprises one or more computer processors to calculate inverted biaxial anisotropy (BA) parameters by performing an iterative BA inversion operation based on the MCI data; and a fracture identification module that comprises one or more computer processors to identify one or more fracture properties of the subsurface formation based at least in part on the MSL data and one or more of the inverted BA parameters, wherein the identification comprises identifying presence of a fracture in the formation by calculating a value of an identification function based on formation parameters calculated from the MCI and MSL data; wherein the identification function is variable as a function of the inverted BA parameters, an inverted TI parameter, and a parameter from the MSL data; wherein the identification further comprises: determining if the value of the identification function meets a threshold value; and based upon the determination, identifying the presence of a fracture in the formation. 13. The system of claim 12 , wherein the inversion module is further configured to calculate inverted transverse isotropy (TI) parameters by performing an iterative inversion operation on the MCI data using a TI formation model that represents simulated formation resistivity characteristics that account for transverse formation isotropy to resistivity. 14. The system of claim 12 , wherein the inversion module calculates the inverted BA using a BA formation model that represents simulated formation resistivity characteristics that account for transverse biaxial formation anisotropy to resistivity. 15. The system of claim 12 , wherein the fracture identification module is further configured to calculate, using one or more processors, a fracture strike or an azimuth angle based on both the MCI and MSL data. 16. A computer readable storage medium having stored thereon instructions for causing a machine, in response to execution of the instructions by the machine, to perform operations comprising: accessing multicomponent induction (MCI) and multipole sonic logging (MSL) data captured by measurement tools in a borehole extending through a subsurface formation; calculating, in an automated procedure using one or more computer processors, inverted biaxial anisotropy (BA) parameters by performing an iterative BA inversion operation based on the MCI data and performing fracture analysis to identify one or more fracture properties of the subsurface formation based at least in part on the MSL data and one or more of the inverted BA parameters, wherein performing the fracture analysis further comprises identifying presence of a fracture in the formation by calculating a value of an identification function based on formation parameters calculated from the MCI and MSL data; wherein the identification function is variable as a function of the inverted BA parameters, an inverted TI parameter, and a parameter from the MSL data; determining if the value of the identification function meets a threshold value; and based upon the determination, identifying the presence of a fracture in the formation.

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Classifications

  • G01V1/50Primary

    Analysing data · CPC title

  • Processing data, e.g. for analysis, for interpretation, for correction · CPC title

  • E21B49/00Primary

    Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells · CPC title

  • Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00 · CPC title

  • specially adapted for well-logging · CPC title

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What does patent US11230922B2 cover?
Evaluation of formation and fracture characteristics based on multicomponent induction (MCI) and multipole sonic logging (MSL) data includes automated calculation of inverted biaxial anisotropy (BA) parameters for the formation by performing an iterative BA inversion operation based on the MCI log data and using a BA formation model that accounts for transfers by axial formation anisotropy to r…
Who is the assignee on this patent?
Halliburton Energy Services Inc
What technology area does this patent fall under?
Primary CPC classification G01V1/50. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jan 25 2022 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).