Method for characterizing a geological formation traversed by a borehole

• US 9,581,723 B2
• Filed: 04/10/2009
• Issued: 02/28/2017
• Est. Priority Date: 04/10/2008
• Status: Expired due to Fees

• Current Assignee: Schlumberger Technology Corporation (SLB)
• Original Assignee: Schlumberger Technology Corporation (SLB)
• Inventors: Hurley, Neil Francis, Zhang, Tuanfeng
• Primary Examiner(s): BREIER, KRYSTINE E
• Application Number:
  US12/384,945
• Publication Number:
  US 20090262603A1
• Time in Patent Office: 2,881 Days
• Field of Search: 367/35, 367/86, 345/419, 702/11, 702/16
• US Class Current: 1/1
• CPC Class Codes: G01V 11/00 Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
• CPC Class Codes: G01V 2210/665 using geostatistical modeling

Abstract

Methods for characterizing a geological formation, the methods include retrieving measured data provided by a measuring tool along one or more logged borehole length for a borehole, another borehole or both in order to produce a borehole imaging log. Selecting depth-defined intervals of the borehole imaging log as training images for inputting in a multi-point geostatistical model. Determining pattern based simulations for each training image using a pixel-based template of the multi-point geostatistical model so as to obtain training image patterns. Using the pattern based simulation of each training image to assign to each of the training image a corresponding training image pattern. Constructing from the training image patterns one or more fullbore image log of a borehole wall of the borehole. Repeat the second to fourth steps through the one or more logged borehole length in order to construct fullbore images from successive, adjacent training images.

Claims

1. A method for characterizing a geological formation traversed by a first borehole, the method comprising:

a) retrieving one or more sets of measured data provided by at least one measuring tool along one or more logged borehole length for one of the first borehole, at least one other borehole or both in order to produce a borehole imaging log, wherein the borehole imaging log has a lateral dimension corresponding to a borehole circumferential direction, wherein the measured data along the lateral dimension is disposed along a plurality of angular sectors covered by electrodes of the at least one measuring tool, and wherein data gaps exist in the borehole imaging log along the lateral dimension between the angular sectors covered by the electrodes of the at least one measuring tool;

b) selecting depth-defined intervals of the borehole imaging log as training images for inputting in a multi-point geostatistical model;

c) determining pattern based simulations for each training image using at least one pixel-based template of the multi-point geostatistical model so as to obtain training image patterns;

d) using the pattern based simulation of each training image to assign to each of the training images a corresponding training image pattern;

e) constructing from the training image patterns one or more fullbore image logs of a borehole wall of the first borehole, wherein constructing the one or more fullbore image logs includes simulating patterns in the data gaps in the borehole imaging log along the lateral dimension; and

f) repeating steps (b) to (e) through the one or more logged borehole length in order to construct fullbore images from successive, adjacent training images.

2. The method according to claim 1, wherein the borehole imaging log includes one of processed raw data that consists of measured values and non-measured values.

3. The method according to claim 1, wherein the borehole imaging log includes one of unidentified borehole image data or data gaps.

4. The method according to claim 3, wherein the one of unidentified borehole image data or data gaps is from the group consisting of one of at least one damaged pad in the reservoir, at least one damaged area in the reservoir, at least one pad with inadequate pad pressure against a borehole wall in the reservoir, at least one pad obstructed from contacting the borehole wall in the reservoir or at least one inoperable pad in the reservoir, electronic malfunctions from the measuring tool or other devices.

5. The method according to claim 3, wherein the determined pattern based simulations for each training image are used to group and then simulate patterns in the data gaps.

6. The method according to claim 1, wherein the one or more set of measured data is from the group consisting of one of logging data having multiple depths of investigation, logging-while-drilling data, wireline logging data or some combination thereof.

7. The method according to claim 1, wherein the constructed fullbore images includes plotting a digital file of the constructed fullbore images onto one of a digital media or hard copy media.

8. The method according to claim 1, wherein pattern based simulations use filter scores.

9. The method according to claim 8, wherein determining the filter scores for each training image includes a filtering process that uses the selected at least one pixel-based template as a filter that processes retrieved one or more set of measured data so as to detect training image patterns, then determines filter scores for each training image pattern.

10. The method according to claim 9, wherein the training image patterns are patterns of pixel associations within the training images that provides filter scores to the neighborhoods around each measured pixel.

11. The method according to claim 1, wherein the training images are oriented as two-dimensional (2D) scalar arrays of continuously variable numerical values.

12. The method according to claim 1, wherein the one or more logged borehole length is one of equal to or less than 1 foot, between 1 to 3 feet, or greater than 3 feet.

13. The method according to claim 1, wherein constructing the fullbore images from successive, adjacent training images includes overlapping each adjacent selected depth-defined intervals of the borehole imaging log.

14. The method according to claim 1, wherein at least one constructed fullbore image allows for a drawing of closed contours around one of at least one dark color patch or at least one light color patch in the borehole images.

15. The method according to claim 14, wherein the at least one dark color patch represents one of electrically non-resistive regions, minimal amplitude of reflected acoustic waves, substantial travel time of reflected acoustic waves, minimal formation density, or some combination thereof.

16. The method according to claim 14, wherein the at least one light color patch represents one of electrically resistive regions, substantial amplitude of reflected acoustic waves, minimal travel time of reflected acoustic waves, substantial formation density or some combination thereof.

23. The method of claim 1, wherein the borehole imaging log is produced from measured data along the first borehole such that the training images and the measured data are obtained from the same borehole.

17. A method using a multi-point geostatistical model for characterizing a geological formation traversed by a borehole, the method comprising:

a) retrieving a set of measured data provided by at least one tool along depth-defined intervals of the borehole in order to produce a borehole imaging log, wherein the borehole imaging log has a lateral dimension corresponding to a borehole circumferential direction, wherein the measured data along the lateral dimension is disposed along a plurality of angular sectors covered by electrodes of the at least one tool, and wherein data gaps exist in the borehole imaging log along the lateral dimension between the angular sectors covered by the electrodes of the at least one tool;

b) selecting depth-defined intervals of the borehole imaging log as training images for inputting in a multi-point geostatistical model;

c) determining filter scores for each training image using a pixel-based template of the multi-point geostatistical model so as to obtain training image patterns;

d) classifying training image patterns based on their filter scores;

e) constructing from the training image patterns one or more fullbore image logs of a borehole wall from the subterranean area, wherein constructing the one or more fullbore image logs includes simulating patterns in the data gaps in the borehole imaging log along the lateral dimension; and

f) repeating steps (b) to (e) through the depth-defined intervals of the borehole in order to construct fullbore images from successive, adjacent training images.

18. The method according to claim 17, wherein the one or more set of measured data is from the group consisting of one of logging data having multiple depths of investigation, logging-while-drilling data, wireline logging data or some combination thereof.

19. The method according to claim 17, wherein determining the filter scores for each training image includes a filtering process that uses the selected at least one pixel-based template as a filter that processes retrieved one or more set of measured data so as to detect training image patterns, then determines filter scores for each training image pattern.

20. The method according to claim 17, wherein constructing the fullbore images from successive, adjacent training images includes overlapping each adjacent selected depth-defined intervals of the borehole imaging log.

21. A storage device readable by a machine and storing a set of instructions executable by the machine to perform method steps for characterizing a geological formation traversed by a borehole, the method comprising:

a) retrieving a set of measured data provided by at least one oilfield application tool along depth-defined intervals of a reservoir in order to produce a borehole imaging log, wherein the borehole imaging log has a lateral dimension corresponding to a borehole circumferential direction, wherein the measured data along the lateral dimension is disposed along a plurality of angular sectors covered by electrodes of the at least one oilfield application tool, and wherein data gaps exist in the borehole imaging log along the lateral dimension between the angular sectors covered by the electrodes of the at least one oilfield application tool;

b) selecting depth-defined intervals of the borehole imaging log as training images for inputting in a multi-point geostatistical model;

c) determining filter scores for each training image using a pixel-based template of the multi-point geostatistical model so as to obtain training image patterns;

d) classifying training image patterns based on their filter scores;

e) constructing from the training image patterns one or more fullbore image logs of a borehole wall from the reservoir, wherein constructing the one or more fullbore image logs includes simulating patterns in the data gaps in the borehole imaging log along the lateral dimension; and

f) repeating steps (b) to (e) through the depth-defined intervals of the reservoir in order to construct fullbore images from successive, adjacent training images.

22. A method for characterizing a geological formation, the method comprising:

a) retrieving one or more set of measured data provided by at least one tool along one or more geological area in order to produce a portion of a complete geological image, wherein the portion of the complete geological image has a lateral dimension corresponding to a borehole circumferential direction, wherein the measured data along the lateral dimension is disposed along a plurality of angular sectors covered by electrodes of the at least one tool, and wherein data gaps exist in the portion of the complete geological image along the lateral dimension between the angular sectors covered by the electrodes of the at least one tool;

b) selecting defined intervals of the portion of the geological image as training images for inputting in a multi-point geostatistical model;

c) determining pattern based simulations for each training image using at least one pixel-based template of the multi-point geostatistical model so as to obtain training image patterns;

d) constructing from the training image patterns one or more complete geological images of the geological area, wherein constructing the one or more complete geological images includes simulating patterns in the data gaps in the portion of the complete geological image along the lateral dimension; and

e) repeat steps (b) to (d) through the one or more geological areas in order to construct complete geological images from successive, adjacent training images.