Discovering hidden geothermal signatures using non-negative matrix factorization with customized \u3ci\u3ek\u3c/i\u3e-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (\u3c90◦C) and medium (90-150◦C)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTens ors/GeoThermalCloud.jl

Intermediate-Scale Hydraulic Fracturing in a Deep Mine - kISMET Project Summary 2016: kISMET Project Summary 2016

In support of the U.S. DOE SubTER Crosscut initiative, we established a field test facility in a deep mine and designed and carried out in situ hydraulic fracturing experiments in the crystalline rock at the site to characterize the stress field, understand the effects of rock fabric on fracturing, and gain experience in monitoring using geophysical methods. The project also included pre- and post-fracturing simulation and analysis, laboratory measurements and experiments, and we conducted an extended analysis of the local stress state using previously collected data. Some of these activities are still ongoing. The kISMET (permeability (k) and Induced Seismicity Management for Energy Technologies) experiments meet objectives in SubTER’s “stress” pillar and the “new subsurface signals” pillar. The kISMET site was established in the West Access Drift of SURF 4850 ft (1478 m) below ground (on the 4850L) in phyllite of the Precambrian Poorman Formation. We drilled and cored five near-vertical boreholes in a line on 3 m spacing, deviating the two outermost boreholes slightly to create a five-spot pattern around the test borehole centered in the test volume at ~1528 m (5013 ft). Laboratory measurements of core from the center test borehole showed P-wave velocity heterogeneity along each core indicating strong, fine-scale (~1 cm or smaller) changes in the mechanical properties of the rock. The load-displacement record on the core suggests that the elastic stiffness is anisotropic. Tensile strength ranges between 3‒7.5 MPa and 5‒12 MPa. Permeability measurements are planned, as are two types of laboratory miniature hydraulic fracturing experiments to investigate the importance of rock fabric (anisotropy and heterogeneity) on near-borehole hydraulic fracture generation. Pre-fracturing numerical simulations with INL’s FALCON discrete element code predicted a fracture radius of 1.2 m for a corresponding injection volume of 1.2 L for the planned fractures, and negligible microseismicity. Field measurements of the stress field by hydraulic fracturing showed that the minimum horizontal stress at the kISMET site averages 21.7 MPa (3146 psi) pointing approximately N-S (356 degrees azimuth) and plunging slightly NNW at 12°. The vertical and horizontal maximum stress are similar in magnitude at 42-44 MPa (6090-6380 psi) for the depths of testing which averaged approximately 1530 m (5030 ft). Hydraulic fractures were remarkably uniform suggesting core-scale and larger rock fabric did not play a role in controlling fracture orientation. Monitoring using ERT and CASSM in the four monitoring boreholes, and passive seismic accelerometer-based measurements in the West Access Drift, was carried out during the generation of a larger fracture (so-called stimulation test) at a depth of 40 m below the invert. ERT was not able to detect the fracture created, nor were the accelerometers in the drift, but microseismicity was detected for first (deepest) hydraulic-fracturing stress measurement. The CASSM data have not yet been analyzed. Analytical solutions suggest fracture radius of the large fracture (stimulation test) was more than 6 m, depending on the unknown amount of leak-off. The kISMET results for stress state are consistent with large-scale mid-continent estimates of stress. Currently we are using the orientation of the stress field we determined to interpret a large number of borehole breakouts recorded in nearby boreholes at SURF to generate a more complete picture of the stress field and its variations at SURF. The efforts on the project have prompted a host of additional follow-on studies that we recommend be carried out at the kISMET site