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At least 163 records · Page 9

Utah FORGE: Well 16A(78)-32 Hydraulic Fracturing Stage 8 Crosswell Strain FDI and Microseismic Presentations - April 2024

This is a pair of PowerPoint presentations from Neubrex Energy Services (US), LLC. The presentations review work done in April 2024 on crosswell strain fracture driven interactions (FDI) and microseismic event monitoring during hydraulic fracturing in stage 8 of Utah FORGE well 16A(78)-32. Well 16B(78)-32 was the monitoring well and was where the data for these presentations were collected.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Wells 16A(78)-32 and 16B(78)-32 Stimulation Program Report - May 2024

This dataset consists of a comprehensive report documenting the stimulation program conducted in May 2024 on Utah FORGE wells 16A(78)-32 and 16B(78)-32. It includes detailed accounts of operational and scientific objectives, stimulation methodologies, and testing outcomes. The report describes the hydraulic fracturing activities, equipment setups, proppant and fluid usage, and the execution of a nine-hour circulation test. It also includes observations from seismic and fiber optic monitoring systems, providing data on microseismic activity and fracture propagation. Detailed parameters for each stimulation stage are provided, alongside operational challenges and solutions. The dataset includes analyses of injection and production rates, well temperatures, and pressure data, supported by graphical illustrations and logs.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Temperature-Dependent Fracture Seismicity from Fluid Injection Experiments

This dataset contains experimental data from fluid injection experiments conducted to investigate the influence of temperature on fracture seismicity. The experiments were performed on granite samples from Utah FORGE. The samples were prepared with a 30-degree inclined fracture and subjected to controlled stress and temperature conditions. Data were collected under three distinct temperature settings: 24 C, 78 C, and 137 C. During the experiments, a constant confining pressure of 10 MPa and a constant shear stress at 80% of the shear strength of the sample were maintained. Pore pressure was incrementally increased at a rate of 300 kPa every three minutes to simulate fluid injection. Temperature was raised rapidly and then stabilized for the duration of each test. The dataset includes shear stress and displacement measurements under each temperature condition, along with supplementary figures illustrating the experimental setup and time-series plots of pressures and temperature.

15 GEOTHERMAL ENERGY↗

Utah FORGE: RESMAN Well 16A(78)-32 and 16B(78)-32 Stimulation and Circulation Tracer Test Results - 2024

This dataset contains tracer test results from stimulation and circulation experiments conducted on the Utah FORGE wells 16A(78)-32 and 16B(78)-32 during 2024. The data was collected by RESMAN Energy Technology and includes detailed tracer analysis from flowback, short- and extended-duration circulation tests, and reinjection sampling. Sampling included analysis of tracers during different stages of testing in April, August, and September 2024. The dataset is accompanied by an interpretation report and contains time-series tracer concentration data with identification of test phases and sampling conditions. It includes results for flowback from well 16A, commingling effects with water from well 16B, tracer data from short and extended circulation tests, and reinjection tracer corrections for the August/September test. Users should be aware that proprietary tracer methodologies were applied, and they should consult the interpretation report for insights into experimental procedures and data contextualization.

15 GEOTHERMAL ENERGY↗

Utah FORGE: EGS Reservoir Produced Fluids Geochemistry 2022-2024

This dataset contains geochemical analyses of produced fluids from the Utah FORGE site, specifically from wells 16A(78)-32, 16B(78)-32, and 58-32, collected during various stimulation, flowback, and circulation tests conducted between 2022 and 2024. The data contains element concentrations, pH, and dissolved gas compositions. Geochemical analyses for 2022 and 2023 were performed at the Brigham Young University geochemistry laboratory, while the 2024 results were obtained from Thermochem. Dry gas samples were collected using a mini-separator attached to the single-phase production line between the wellhead and separator, where fluid was flashed to atmospheric pressure. Gas concentrations were recalculated to a single phase reservoir liquid based on heat and mass balance expressions. Additional contextual information, including interpretations of geochemical trends and reservoir behavior, is available in the included report from Simmons et al. (2025), which was presented at the Stanford Geothermal Workshop in February 2025.

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Utah FORGE: Triaxial Direct Shear Results - February 2025

This dataset contains results from nine triaxial direct shear tests conducted by Los Alamos National Laboratory on samples from FORGE Well 16A(78)-32. The primary objectives of this work were to determine the shear strength in both intact and residual states, evaluate dilation against displacement, assess permeability in relation to displacement, time, and normal stress, understand the relationship between aperture and normal stress, and monitor the effluent chemistry as a function of time. The data includes time-series measurements of stress, displacement, permeability, and effluent chemistry, with and without experimental dilution corrections. Additional materials include profilometry data, photographic documentation of the experimental setups and apparatus, and test notes. The dataset is organized into folders corresponding to each test, containing hydromechanical data, effluent chemistry measurements, and images. The hydromechanical data consists of detailed time-series records capturing parameters such as shear force, confining pressure, permeability, and temperature. Effluent chemistry data tracks fluid composition changes over time. Also included are conference papers, presentation slides, and a summary document outlining the experiments.

15 GEOTHERMAL ENERGY↗

Utah FORGE: 16B(78)-32 RFS DSS Strain Change Rate vs. Depth During 16A(78)-32 Stimulation

This dataset contains strain change rate versus depth data acquired using a Rayleigh frequency shift (RFS) distributed strain sensing (DSS) system during hydraulic stimulation of well 16A(78)-32 at the Utah FORGE site in April 2024. The data were collected from an optical fiber installed in the annulus of production well 16B(78)-32, approximately 300 feet from the injection well. The dataset includes tabulated strain data and an explanation of the methodology used to generate the frac log, which integrates strain change rate signals over selected time windows to identify fracture events.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Well 16B(78)-32 DTS, RFS DSS Strain, and Absolute Strain Circulation Test Fiber Optic Data - August 2024

This dataset contains processed fiber optic measurements collected during the extended cross-well circulation test at the Utah FORGE site in August 2024. The data was acquired from the 16B(78)-32 well using distributed fiber optic sensing (DFOS) technology, including distributed temperature sensing (DTS) on multimode fiber and distributed strain sensing (DSS) measurements on single-mode fiber. The dataset includes Brillouin absolute strain, Rayleigh frequency shift (RFS) DSS strain change, RFS DSS strain change rate, and temperature (DTS) data, all stored in HDF5 format. Time coordinates are provided in UTC, and depth measurements are given in measured depth relative to the rotary kelly bushing (MD RKB) in feet. The spatial sampling on the RFS DSS strain data and the Brillouin Absolute Total Strain data is 20 cm and the spatial sampling on the DTS data is 1m. The dataset is accompanied by a report from Neubrex, which provides further documentation.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Seismic DAS and Geophone Borehole Data Processing and 3D Imaging of Vp/Vs Ratio in the 2024 Stimulated Reservoir

This dataset includes a final report and a 3D velocity model derived from seismic DAS and geophone borehole data collected during the April 2024 stimulation of the reservoir at Utah FORGE. The report details the processing of over 50,000 P- and S-wave travel times used in a tomographic inversion to estimate the Vp/Vs ratio, revealing anomalies adjacent to wells 16A and 16B that may be associated with injected fracturing fluids. Additionally, Wadati analysis of more than 27,000 pairs of differential P- and S-wave travel times supports this interpretation with a high Vp/Vs estimate of 1.86, averaged over the dimensions of the earthquake cluster. The accompanying data file provides a 3D model of P- and S-wave velocities and Vp/Vs ratios, structured with spatial coordinates and velocity values.

15 GEOTHERMAL ENERGY↗

A Mixed Fracture-Matrix Model for Evaluating Well Orientation and Completion Options for the Utah FORGE Site

Orientation and completion for well pairs that have been subjected to multi-zonal stimulation play a critical role in the long-term performance of an Enhanced Geothermal Reservoir. Here we present the development of a methodology to rapidly and efficiently numerically simulate mixed fracture-matrix flow systems for evaluation of well design and completion options. An example evaluation based on a small fracture network representative of FORGE Well 16(A and B)-78(32) follows a discussion of the theory and model validation.

58 GEOSCIENCES↗

Evaluation and Optimization of Well Completion Options for the Utah FORGE Site

Orientation and completion for well pairs that have been subjected to multi-zonal stimulation play a critical role in the long-term performance of an Enhanced Geothermal Reservoir. Enhanced geothermal systems often rely on preferential flow along fractures between well injection and production locations. Modeling this preferential flow using discrete fracture networks (DNF) relies on stochastic realizations of the DFN based on geological sampling. Here we present the development of a stochastic optimization methodology to determine well completion options in a discrete fracture network based on using parallel subset simulation. Stochastic optimization will provide insight into regions where placements of the injection and production wells are optimal. An example optimization of well-pair location optimization based on a deterministic-stochastic DFN model representing FORGE follows a discussion of the theory.

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Geothermal well testing pressure prediction by using a hybrid transformer model system: FORGE well use case

Geothermal has huge potential to become an indispensable component in achieving the goal of sustainable energy economy, given its capability to provide consistent baseload power to the electric grid. Injection tests are crucial in geothermal energy system as they naturally help to evaluate reservoir properties, understand fluid flow and even enhance reservoir performance. In this research, we developed a hybrid model system that integrates machine learning (ML) regression, a physics-based mathematical model, and transformer deep learning. Trained and validated using FORGE injection test dataset, this system can forecast the pressure variations both upward and downward over time. The pressure prediction achieved prediction accuracy within 3-6% variance of true pressure values. The system can significantly save time and reduce costs by testing only a few cycles and then using model predictions for further analysis, instead of conducting additional real injection cycle tests. The developed model system also holds promise for designing injection test processes and maintaining well production in geothermal energy. Presented at the IMAGE ‘25 Conference led by Shell.

FORGE↗

In Situ X-ray Diffraction Investigation of Hydrogen Effects on Deformation-Induced Phase Transformation in Forged and Additively Manufactured 304L Stainless Steels

Here, this study utilized high energy synchrotron x-ray diffraction to probe microstructural evolution during uniaxial deformation of conventionally manufactured and additively manufactured (AM) 304L stainless steel with and without internal hydrogen. The objective of this effort is to highlight the effect of hydrogen on deformation-induced martensite phase transformations in austenitic stainless steels. Solute hydrogen depresses the required applied strain to initiate austenite transformation to ε-martensite and α'-martensite in both forged and AM stainless steel. Similarly, the total fraction of transformation product is larger when the microstructure is saturated with hydrogen. Deformation induced phase transformations also lead to a variation in strain partitioning behavior, which is linked to the chemical composition and stacking fault energy of the starting and hydrogen-charged materials.

36 MATERIALS SCIENCE↗

Seismic monitoring of EGS fracture stimulations at Utah FORGE (Part 1): Time-lapse variations of b-values and Shear-wave Splitting Rates of induced microearthquakes

Characterizing geologic formations near geothermal wells is crucial for efficient extraction of subsurface geothermal energy resources. To monitor effective fracture stimulation of enhanced geothermal systems (EGS), we analyze a catalog of induced microearthquakes to characterize seismicity induced by Phase 2C fracture stimulations of the Utah FORGE project and derive the b-values for 424 induced microearthquakes in three stages of fracture stimulation. Here, we find the time-lapse variations of these b-values. We apply eigenvector rotation and waveform correlation to 3C geophone data to separate fast S 1 and slow S 2 waves, determine their directions, measure their lag time, and calculate the S-wave splitting rate (SSR) for six induced microearthquakes in Stage 1 and 21 in Stage 3. Both SSR values and b-values increase with time. The increase in these values may be related to heavily fractured zones created by fracture stimulations during Stage 2 injections. Large and highly variable SSR values in Stage 3 may reflect heterogeneities in the fracture zones. Time-lapse variations of SSR values and b-values may be one of the most useful approaches to monitoring and characterizing the effectiveness and efficiency of various types of fracture stimulations.

58 GEOSCIENCES↗

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗

Utah FORGE 1-2409: PetroQuip Energy Services Zonal Isolation Solution for Geothermal Wells - 2024 Annual Workshop Presentation

This is a presentation on the Zonal Isolation Solution for Geothermal Wells by PetroQuip Energy Services, presented by Robert Coon. This video slide presentation discusses the proposed design and development of a multi-stage system consisting of an Open-Hole Packer (OHP), a Locking Bridge Plug (LBP), and a corresponding Locating Profile (LP). This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

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