Field data acquisition and virtual training system
A method includes obtaining data representing a subterranean volume, the data having been collected by a user in a field, generating a digital model representing at least the subterranean volume based in part on the data, searching the digital model based in part on one or more metadata parameters, identifying one or more gaps in the model, and determining a data acquisition activity based on the one or more gaps that were identified in the model.
1. A method comprising:
obtaining data representing a subterranean volume, the data having been collected by a user in a field;
generating a digital model representing at least the subterranean volume based in part on the data;
searching the digital model based in part on one or more metadata parameters, the one or more metadata parameters describing one or more characteristics of a target location;
identifying, based on the searching, a plurality of analogous locations in the digital model based on the one or more characteristics of the target location;
prioritizing a first analogous location included in the plurality of analogous locations over a second analogous location included in the plurality of analogous locations based on a geographic relationship between the first analogous location and the target location;
identifying, based on the searching, one or more gaps in the digital model; and
determining a data acquisition activity based on the one or more gaps that were identified in the digital model.
2. The method of claim 1 , further comprising applying metadata to data in the digital model, wherein the metadata include text-based information about the data in association with a location in the digital model, and wherein searching the digital model comprises searching the text-based information of the metadata.
3. The method of claim 1 , wherein generating the digital model comprises georeferencing the data and incorporating the data into the digital model based at least in part on the georeferencing, wherein the digital model includes other data representing the subterranean volume, another subterranean volume, or both.
4. The method of claim 1 , wherein generating the digital model comprises discretizing the data so as to form a discretized model comprising a plurality of cells.
5. The method of claim 1 , further comprising:
generating a three-dimensional visualization based at least in part on the digital model; and
generating an immersive training environment using the three-dimensional visualization.
6. The method of claim 1 , wherein generating the digital model comprises:
augmenting the data using a well log; and
incorporating the well log in the digital model along a line in the digital model.
7. The method of claim 1 , further comprising:
receiving additional data collected as a result of the data acquisition activity; and
updating the digital model based in part on the additional data collected.
8. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations, the operations comprising:
obtaining data representing a subterranean volume, the data having been collected by a user in a field;
generating a digital model representing at least the subterranean volume based in part on the data;
searching the digital model based in part on one or more metadata parameters, the one or more metadata parameters describing one or more characteristics of a target location;
identifying, based on the searching, a plurality of analogous locations in the digital model based on the one or more characteristics of the target location;
prioritizing a first analogous location included in the plurality of analogous locations over a second analogous location included in the plurality of analogous locations based on a geographic relationship between the first analogous location and the target location;
identifying, based on the searching, one or more gaps in the digital model; and
determining a data acquisition activity based on the one or more gaps that were identified in the digital model.
9. The medium of claim 8 , wherein the operations further comprise applying metadata to data in the digital model, wherein the metadata include text-based information about the data in association with a location in the digital model, and wherein searching the digital model comprises searching the text-based information of the metadata.
10. The medium of claim 8 , wherein generating the digital model comprises georeferencing the data and incorporating the data into the digital model based at least in part on the georeferencing, wherein the digital model includes other data representing the subterranean volume, another subterranean volume, or both.
11. The medium of claim 8 , wherein generating the digital model comprises discretizing the data so as to form a discretized model comprising a plurality of cells.
12. The medium of claim 8 , wherein the operations further comprise:
generating a three-dimensional visualization based at least in part on the digital model; and
generating an immersive training environment using the three-dimensional visualization.
13. The medium of claim 8 , wherein generating the digital model comprises:
augmenting the data using a well log; and
incorporating the well log in the digital model along a line in the digital model.
14. The medium of claim 8 , wherein the operations further comprise:
receiving additional data collected as a result of the data acquisition activity; and
updating the digital model based in part on the additional data collected.
15. A computing system, comprising:
one or more processors; and
a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising:
obtaining data representing a subterranean volume, the data having been collected by a user in a field;
generating a digital model representing at least the subterranean volume based in part on the data;
searching the digital model based in part on one or more metadata parameters, the one or more metadata parameters describing one or more characteristics of a target location;
identifying, based on the searching, a plurality of analogous locations in the digital model based on the one or more characteristics of the target location;
prioritizing a first analogous location included in the plurality of analogous locations over a second analogous location included in the plurality of analogous locations based on a geographic relationship between the first analogous location and the target location;
identifying, based on the searching, one or more gaps in the digital model; and
determining a data acquisition activity based on the one or more gaps that were identified in the digital model.
16. The computing system of claim 15 , wherein the operations further comprise applying metadata to data in the digital model, wherein the metadata include text-based information about the data in association with a location in the digital model, and wherein searching the digital model comprises searching the text-based information of the metadata.
17. The computing system of claim 15 , wherein generating the digital model comprises georeferencing the data and incorporating the data into the digital model based at least in part on the georeferencing, wherein the digital model includes other data representing the subterranean volume, another subterranean volume, or both.