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This is the Utah FORGE well 16A(78)-32 stimulation microseismic detection and location report from Silixa LLC. The stimulation was accomplished during April, 2022.
This Excel spreadsheet contains temperature survey results for Utah FORGE wells 58-32, 78-32, 56-32, 16A(78)-32 and 78B-32. It also contains charts and comparisons, along with a "Data Summary" which provides links to previous GDR submissions with temperature data for each well.
This archive contains data from the tracer test performed during the Utah FORGE well 16A(78)-32 stimulation. This includes: 1. the raw data file from Pason in the csv format; 2. a one-page Word document from Pason that explains the headers and units used in their data file; 3. an Excel spreadsheet with concentration data and relevant Pason flow data; 4. a Word document with jpg versions of concentration charts (Figs. 1-3) and a tracer mass recovery chart (Fig. 4).
Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, formerly FS-C, and FS02, formerly FS1-2) in human-readable comma-separated value text files. There are two header lines in each file describing the data contained in that column along with their units, respectively. Data have been decimated from 2 to 1 Hz to match the Pason data found in the linked GDR dataset below (16A78-32 Stimulation Pason Data). These files contain the time series spanning the same time interval as the Pason data as well as ambient data for 5 hours before the stimulation and 5 hours following shut in. The station locations were chosen based on their proximity to the borehole seismometers owned and operated by the University of Utah. See README.txt for more information.
This submission presents the weekly geochemistry data of the long-term flow test performed within EGS Collab Experiment 1 from early 2019 to early 2020. The fluids from each producing borehole/interval (PI, PB, PDT and PST) along with the injectate were sampled roughly weekly from April 2019 to January 2020 for geochemistry analysis. The geochemical measurement was part of a long-term microbial profiling project (see details in the PNAS paper linked below). Additional background and methodologies are available in the PNAS paper linked bellow.
The following folders contain 3 friction experiments on Utah FORGE core material from depths of 6735 - 8533ft. The experiment conditions range from 100% relative humidity at room temperature to fluid-saturated at 110C. Experiments were done on both intact samples in a single-direct shear configuration, double-direct shear, and gouge.
Multiple sets of tracer tests were conducted at the EGS Collab Testbed 2 on the 4100 L at the Sanford Underground Research Facility (SURF), Lead, SD. The enclosed data package includes: tracer recovery results, water balance calculations and rationales, water flow measurement for north ditch, (manual) water flow measurements at different production points, and a tracer-interpretation paper presented at the Stanford Geothermal Workshop, 2023.
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This GDR submission includes those weights. The weighting was done using two different approaches: one based on expert opinions, and one based on statistical learning. The weights are intended to describe how useful a particular exploration method is for imaging each component of each play type. They may be adjusted based on the characteristics of the resource under investigation, knowledge of the quality of the dataset, or simply to reduce the impact a single dataset has on the resulting outputs. Within the DEEPEN PFA, separate sets of weights are produced for each component of each play type, since exploration methods hold different levels of importance for detecting each play component, within each play type. The weights for conventional hydrothermal systems were based on the average of the normalized weights used in the DOE-funded PFA projects that were focused on magmatic plays. This decision was made because conventional hydrothermal plays are already well-studied and understood, and therefore it is logical to use existing weights where possible. In contrast, a true PFA has never been applied to superhot EGS or supercritical plays, meaning that exploration methods have never been weighted in terms of their utility in imaging the components of these plays. To produce weights for superhot EGS and supercritical plays, two different approaches were used: one based on expert opinion and the analytical hierarchy process (AHP), and another using a statistical approach based on principal component analysis (PCA). The weights are intended to provide standardized sets of weights for each play type in all magmatic geothermal systems. Two different approaches were used to investigate whether a more data-centric approach might allow new insights into the datasets, and also to analyze how different weighting approaches impact the outcomes. The expert/AHP approach involved using an online tool (https://bpmsg.com/ahp/) with built-in forms to make pairwise comparisons which are used to rank exploration methods against one-another. The inputs are then combined in a quantitative way, ultimately producing a set of consensus-based weights. To minimize the burden on each individual participant, the forms were completed in group discussions. While the group setting means that there is potential for some opinions to outweigh others, it also provides a venue for conversation to take place, in theory leading the group to a more robust consensus then what can be achieved on an individual basis. This exercise was done with two separate groups: one consisting of U.S.-based experts, and one consisting of Iceland-based experts in magmatic geothermal systems. The two sets of weights were then averaged to produce what we will from here on refer to as the "expert opinion-based weights," or "expert weights" for short. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. More information on this approach along with the dataset used to produce the statistical weights may be found in the linked dataset below.
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), index models needed to be developed to map values in geoscientific exploration datasets to favorability index values. This GDR submission includes those index models. Index models were created by binning values in exploration datasets into chunks based on their favorability, and then applying a number between 0 and 5 to each chunk, where 0 represents very unfavorable data values and 5 represents very favorable data values. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type. Index models were created using histograms of the distributions of each exploration dataset in combination with literature and input from experts about what combinations of geophysical, geological, and geochemical signatures are considered favorable at Newberry. This is in attempt to create similar sized bins based on the current understanding of how different anomalies map to favorable areas for the different types of geothermal plays (i.e., conventional hydrothermal, superhot EGS, and supercritical). For example, an area of partial melt would likely appear as an area of low density, high conductivity, low vp, and high vp/vs. This means that these target anomalies would be given high (4 or 5) index values for the purpose of imaging the heat source. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type. Index models were produced for the following datasets: - Geologic model - Alteration model - vp/vs - vp - vs - Temperature model - Seismicity (density*magnitude) - Density - Resistivity - Fault distance - Earthquake cutoff depth model
This dataset is a collection of well logs provided by Schlumberger Technologies from the Utah FORGE well 16B(78)-32 drilling project. Information here includes critical borehole information collected by an ultrasonic borehole imager (UBI) and a fullbore formation microimager (FMI). Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The total depth measured 10,947 feet and the vertical depth measured 8,357 feet.
Included here are a presentation recording, slides, and report on the Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores project by Colorado School of Mines, presented by Dr. William W. Fleckenstein. One goal of the project is to develop and demonstrate the use of low-cost, rapid multistage fracture stimulation technology with cemented casing frac sleeves that eliminates packers used in both conventional stimulation and injection flow control. The second goal is to develop and demonstrate the devices to effectively detect and control the flow of heat-carrier fluid solely from a long-reach injector through the network of induced and existing fractures and produced from an open-hole long-reach well to improve heat recovery. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.
This dataset includes microseismic surface network catalogs for Utah FORGE. Data were recorded during the stimulation of well 16A(78)-32 in 2022 and the circulation tests between wells 16A(78)-32 and 16B(78)-32 in 2023. Near-surface seismic monitoring during circulation experiments in wells 16A(78)-32 and 16B(78)-32 revealed fracture growth after shut-in. The catalog provided here offers a comprehensive list of microseismic events, including details on their spatial and temporal distribution, magnitude, and clustering behavior.
These are production logging tests (PLT) results from Halliburton collected during the nine hour circulation test performed at Utah FORGE on April 27th, 2024. The circulation test involved injecting into well 16A(78)-32 and producing out of well 16B(78)-32) and was carried out after the fracturing of both of those wells. Data attached here includes raw and processed PLT logs from both wells, as well as technical reports summarizing the data collection and results.
This dataset consists of Baker Hughes Pressure-Temperature gauge readings on fiber optics in Utah FORGE Well 16B(78)-32. This gauge is at a measured depth of 7,056.67 feet. The true vertical depth can be determined from the well survey data, which is linked below. The data consists of time series pressure-temperature data and plots from March 26th - April 20th 2024.
This dataset consists of all of the pressure pumping data for Utah FORGE Well16A78-32 fracturing stages, Well 16B78-32 fracturing stages, and a 9-hour circulation test which took place after all of the frac plugs were drilled out. Fracturing in the wells took place in stages from April 3rd to April 17th, while the circulation test occurred on April 27th, 2024. Data is in excel files, with ReadMe files for each of the .zip folders that detail what data is available. Also attached here is wellhead pressure data from Pason that is referred to in the ReadMe files.
This is a presentation on Closing the Loop Between In-Situ Stress Complexity and EGS Fracture Complexity by Lawrence Livermore National Laboratory, presented by Matteo Cusini. The video discusses the combination of high-fidelity simulations and true-triaxial block fracturing tests to explore the intricate relationship between in-situ stress and hydraulic fracture patterns. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.
This is a presentation on the Design and Implementation of a Novel Multi-Frac Stimulation Concept by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the design and implementation of a reservoir stimulation concept improving near-wellbore and well-to-well conductivity while enhancing the SRV and promoting self-propping and heat exchange. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13-15, 2024.
This is a presentation on the Development and Testing of Tagged Proppant for Fracture Conductivity Enhancement and Reservoir Characterization in EGS by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the development and testing of new proppants that can be used in geothermal conditions of at least 250 degrees C and at differential pressures of 35-70 MPa. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13-15, 2024.