Authors / CoAuthors
Lawley, C.J.M. | Gadd, M.G. | Parsa, M. | Lederer, G.W. | Graham, G.E. | Ford, A.
Abstract
<div>Geological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.</div><div><br></div><div><strong>Citation: </strong>Lawley, C. J. M., Gadd, M. G., Parsa, M., Lederer, G. W., Graham, G. E., and Ford, A., 2023, Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling: Natural Resources Research. https://doi.org/10.1007/s11053-023-10216-1</div>
Product Type
document
eCat Id
147637
Contact for the resource
Resource provider
Point of contact
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Point of contact
Keywords
- ( Project )
-
- critical minerals mapping initiative
-
- critical minerals
-
- mineral systems
-
- natural language processing
- theme.ANZRC Fields of Research.rdf
-
- GeologyData mining and knowledge discovery
-
- Published_External
Publication Date
2023-06-13T01:20:35
Creation Date
2023-01-12T16:00:00
Security Constraints
Legal Constraints
Status
completed
Purpose
Manuscript examining the use of natural language processing for improving understanding of mineral systems and mineral prospectivity. Case studies are presented for evaluating prospectivity for critical minerals in Canada, United States, and Australia.
Maintenance Information
notPlanned
Topic Category
geoscientificInformation
Series Information
Natural Resources Research
Lineage
<div>Multiple geological databases were used as the basis for generating natural language processing workflows to evaluate mineral prospectivity for critical minerals in Canada, the United States, and Australia.</div>
Parent Information
Extents
[, , , ]
Reference System
Spatial Resolution
Service Information
Associations
Source Information