Data-quality evaluation of calculated true reservoir resistivity

Patent metadata

Field	Value
Publication number	US-10422918-B2
Application number	US-201615512418-A
Country	US
Kind code	B2
Filing date	Apr 26, 2016
Priority date	Apr 26, 2016
Publication date	Sep 24, 2019
Grant date	Sep 24, 2019

Abstract

Disclosed herein are embodiments of systems, methods, and computer program products for assessing the data-quality of the calculated reservoir-rock resistivity R sd in laminar formations. For instance, in one embodiment, a computer-implemented method for assessing the data-quality of the calculated reservoir-rock resistivity R sd in laminar formations comprises the steps of receiving multi-component induction (MCI) data and other sensor logs data associated with a laminar formation; determining a set of calculated reservoir-rock resistivity R sd using at least one of the multi-component induction (MCI) data and other sensor logs data; and performing data quality assessments of the set of calculated reservoir-rock resistivity R sd.

First claim

The invention claimed is:

1. A computer-implemented method for use with a downhole logging tool for assessing the data-quality of at least one of a calculated reservoir-rock resistivity R_sd and reservoir-rock conductivity C_sd in laminar formations, the computer-implemented method comprising:
receiving from a multi-component induction (MCI) tool MCI data associated with a laminar formation and data of sensor logs associated with the laminar formation;
determining at least one of a set of calculated reservoir-rock resistivity R_sd and a set of calculated reservoir-rock conductivity C_sd using at least one of the multi-component induction (MCI) data and other sensor logs data;
performing data quality assessments using a standard deviation of the at least one of the set of calculated reservoir-rock resistivity R_sd and the set of calculated reservoir-rock conductivity C_sd; and
using the standard deviation as a quality indicator for the set of calculated reservoir-rock resistivity R_sd;
wherein the calculated reservoir-rock resistivity R_sd and reservoir-rock conductivity C_sd are calculated using at least one of a bimodal rock-physics model, induction-logging forward model, V1D isotropic formation model, and OD isotropic formation model.

2. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a first reservoir-rock resistivity R_sd from the horizontal resistivity R_h and vertical resistivity R_v logs based on the multi-component induction (MCI) data.

3. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data only.

4. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data and the MCI data.

5. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data and porosity logs.

6. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a reservoir-rock resistivity R_sd from macro-resistivity borehole imager logs and porosity logs.

7. The computer-implemented method according to claim 1 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining a reservoir-rock resistivity R_sd from a combination of two or more selected from the group of array compensated true resistivity (ACRt) log data, the MCI data, macro-resistivity borehole imager logs and porosity logs, and conventional logs.

8. The computer-implemented method according to claim 2 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data further comprises determining a second reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data only.

9. The computer-implemented method according to claim 8 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data further comprises determining a third reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data and the MCI data.

10. The computer-implemented method according to claim 9 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data further comprises determining a fourth reservoir-rock resistivity R_sd from array compensated true resistivity (ACRt) log data and porosity logs.

11. The computer-implemented method according to claim 10 , wherein determining the set of calculated reservoir-rock resistivity R_sd using at least one of the multi-component induction (MCI) data and other sensor logs data further comprises determining a fifth reservoir-rock resistivity R_sd from macro-resistivity borehole imager logs and porosity logs.

12. A system for use with a downhole logging tool for assessing the data-quality of at least one of a calculated reservoir-rock resistivity R_sd and reservoir-rock conductivity C_sd in laminar formations, the system comprising:
a data storage component for storing data and executable instructions;
a processor configured to execute the executable instructions to:
receive from a multi-component induction (MCI) tool MCI data associated with a laminar formation and data of sensor logs associated with the laminar formation;
determine at least one of a set of calculated reservoir-rock resistivity R_sd and a set of calculated reservoir-rock conductivity C_sd using at least one of the multi-component induction (MCI) data and other sensor logs data; and
perform data quality assessments using a standard deviation of the at least one of the set of calculated reservoir-rock resistivity R_sd and the set of calculated reservoir-rock conductivity C_sd; and
using the standard deviation as a quality indicator for the set of calculated reservoir-rock resistivity R_sd;
wherein the calculated reservoir-rock resistivity R_sd and reservoir-rock conductivity C_sd are calculated using at least one of a bimodal rock-physics model, induction-logging forward model, V1D isotropic formation model, and OD isotropic formation model.

13. The system according to claim 12 , wherein the executable instructions to determine the at least one of a set of calculated reservoir-rock resistivity R_sd and a set of calculated reservoir-rock conductivity C_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining at least one of a first reservoir-rock resistivity R_sd from the horizontal resistivity R_h and vertical resistivity R_v logs based on the multi-component induction (MCI) data, and a first reservoir-rock conductivity C_sd from the horizontal conductivity C_h and vertical conductivity C_v logs based on the multi-component induction (MCI) data.

14. The system according to claim 12 , wherein the executable instructions to determine the at least one of a set of calculated reservoir-rock resistivity R_sd and a set of calculated reservoir-rock conductivity C_sd using at least one of the multi-component induction (MCI) data and other sensor logs data comprises determining at least one of a reservoir-rock resistivity R_sd and a reservoir-rock conductivity C_sd from array compensated true resistivity (ACRt) log data only.

15. The system according to claim 12 , wherein the executable instructions to determine the at least one of a set of calculated reservoir-rock resistivity R_sd and a set of calculated reservoir-rock conductiv

Assignees

• Halliburton Energy Services Inc

Inventors

• Hou Junsheng

Classifications

• G01V11/00

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

• G01V3/38 Primary

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

• G01V3/20

  operating with propagation of electric current · CPC title