SYSTEM AND METHOD FOR AUTOMATIC CONVERSION OF INTERPRETED FEATURES ON BOREHOLE IMAGES TO DIGITAL LABELING FOR DEEP LEARNING

1 . A method, comprising:

obtaining N≥1 borehole images, wherein N is an integer;

locating, in each borehole image within the N borehole images, one or more geological features associated with the borehole image; and

determining, for each borehole image within the N borehole images, one or more descriptors associated with the borehole image, each descriptor of the one or more descriptors comprising an optimum polygon enclosing a geological feature of the one or more geological features associated with the borehole image.

2 . The method of claim 1 wherein N≥2, further comprising:

constructing a training dataset of training examples, each training example within the training dataset comprising:

a borehole image from the N borehole images, and

the one or more descriptors associated with the borehole image; and;

training, using the training dataset, an artificial intelligence (AI) model configured to receive, as input, a candidate borehole image and return, as output, one or more candidate descriptors associated with the candidate borehole image, each candidate descriptor within the one or more candidate descriptors comprising a candidate polygon.

3 . The method of claim 2 , further comprising:

selecting a first borehole image from the N borehole images;

determining, using the AI model with the first borehole image as input, one or more predicted descriptors associated with the first borehole image;

selecting a first predicted descriptor within the one or more predicted descriptors, the first predicted descriptor comprising a first predicted polygon;

making a first determination whether a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon;

upon determining that a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon, making a second determination whether the new geological feature belongs to the one or more geological features associated with the first borehole image; and

upon determining that the new geological feature does not belong to the one or more geological features associated with the first borehole image, performing an extension procedure, comprising:

determining a new descriptor associated with the first borehole image, the new descriptor comprising a new optimum polygon enclosing the new geological feature, and

appending the new descriptor to the one or more descriptors associated with the first borehole image.

4 . The method of claim 2 , further comprising:

obtaining an instance borehole image of an instance borehole, the N borehole images not comprising the instance borehole image;

determining, using the AI model with the instance borehole image as input, one or more inferred descriptors associated with the instance borehole image;

determining, based on the one or more inferred descriptors, a geological map of a vicinity of the borehole.

5 . The method of claim 2 , wherein the AI model includes a neural network.

6 . The method of claim 1 , wherein the one or more geological features comprise one or more of:

a fracture;

a vug; and

a nodule.

7 . The method of claim 1 , wherein the optimum polygon is determined by using an optimizer based on a coherency of the borehole image.

8 . The method of claim 1 , wherein each descriptor within the one or more descriptors further comprises a label for the geological feature enclosed by the optimum polygon in the descriptor.

9 . A system, comprising:

a borehole data acquisition system configured to acquire borehole data from N≥1 boreholes, wherein N is an integer;

a borehole imager, configured to determine N borehole images, each borehole image within the N borehole images determined from borehole data for a distinct borehole within the N boreholes;

a geological locator, configured to locate, in a borehole image, one or more geological features associated with the borehole image;

a computer comprising one or more computer processors, configured to:

receive the N borehole images from the borehole imager;

locate, using the geological locator, in each borehole image within the N borehole images, one or more geological features associated with the borehole image; and

determine, for each borehole image of the N borehole images, one or more descriptors associated with the borehole image, each descriptor of the one or more descriptors comprising an optimum polygon enclosing a geological feature of the one or more geological features associated with the borehole image.

10 . The system of claim 9 wherein N≥2, wherein the computer is further configured to:

construct a training dataset of training examples, each training example within the training dataset comprising:

a borehole image from the N borehole images, and

the one or more descriptors associated with the borehole image; and;

train, using the training dataset, an artificial intelligence (AI) model configured to receive, as input, a candidate borehole image and return, as output, one or more candidate descriptors associated with the candidate borehole image, each candidate descriptor of the one or more candidate descriptors comprising a candidate polygon.

11 . The system of claim 10 , wherein the computer is further configured to:

select a first borehole image from the N borehole images;

determine, using the AI model with the first borehole image as input, one or more predicted descriptors associated with the first borehole image;

select a first predicted descriptor of the one or more predicted descriptors, the first predicted descriptor comprising a first predicted polygon;

make a first determination whether a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon;

upon determining that a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon, make a second determination whether the new geological feature belongs to the one or more geological features associated with the first borehole image; and

upon determining that the new geological feature does not belong to the one or more geological features associated with the first borehole image, perform an extension procedure, comprising:

determining a new descriptor associated with the first borehole image, the new descriptor comprising a new optimum polygon enclosing the new geological feature, and

appending the new descriptor to the one or more descriptors associated with the first borehole image.

12 . The system of claim 10 , further comprising a mapping system, configured to:

receive an instance borehole image of an instance borehole, the N borehole images not comprising the instance borehole image;

determine, using the AI model with the instance borehole image as input, one or more inferred descriptors associated with the instance borehole image;

determine, based on the one or more inferred descriptors, a geological map of a vicinity of the borehole.

13 . The system of claim 10 , wherein the AI model includes a neural network.

14 . The system of claim 9 , wherein the one or more geological features comprise one or more of:

a fracture;

a vug; and

a nodule.

15 . The system of claim 9 , wherein the optimum polygon is determined by using an optimizer based on a coherency of the borehole image.

16 . The system of claim 9 , wherein each descriptor of the one or more descriptors further comprises a label for the geological feature enclosed by the optimum polygon in the descriptor.

17 . A non-transitory computer-readable memory comprising computer-executable instructions stored thereon that, when executed on a processor, cause the processor to perform steps comprising:

obtaining N≥1 borehole images, wherein N is an integer;

locating, in each borehole image of the N borehole images, one or more geological features associated with the borehole image; and

determining, for each borehole image of the N borehole images, one or more descriptors associated with the borehole image, each descriptor of the one or more descriptors comprising an optimum polygon enclosing a geological feature of the one or more geological features associated with the borehole image.

18 . The non-transitory computer-readable memory of claim 17 , the steps further comprising:

constructing a training dataset of training examples, each training example within the training dataset comprising:

a borehole image from the N borehole images, and

the one or more descriptors associated with the borehole image; and;

training, using the training dataset, an artificial intelligence (AI) model configured to receive, as input, a candidate borehole image and return, as output, one or more candidate descriptors associated with the candidate borehole image, each candidate descriptor of the one or more candidate descriptors comprising a candidate polygon.

19 . The non-transitory computer-readable memory of claim 18 , the steps further comprising:

selecting a first borehole image from the N borehole images;

determining, using the AI model with the first borehole image as input, one or more predicted descriptors associated with the first borehole image;

selecting a first predicted descriptor of the one or more predicted descriptors, the first predicted descriptor comprising a first predicted polygon;

making a first determination whether a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon;

upon determining that a new geological feature, in the first borehole image, intersects an area delimited by the first predicted polygon, making a second determination whether the new geological feature belongs to the one or more geological features associated with the first borehole image; and

upon determining that the new geological feature does not belong to the one or more geological features associated with the first borehole image, performing an extension procedure, comprising:

determining a new descriptor associated with the first borehole image, the new descriptor comprising a new optimum polygon enclosing the new geological feature, and

appending the new descriptor to the one or more descriptors associated with the first borehole image.

20 . The non-transitory computer-readable memory of claim 18 , the steps further comprising:

obtaining an instance borehole image of an instance borehole, the N borehole images not comprising the instance borehole image;

determining, using the AI model with the instance borehole image as input, one or more inferred descriptors associated with the instance borehole image;

determining, based on the one or more inferred descriptors, a geological map of a vicinity of the borehole.