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At least 109 records · Page 6

Field Experiments and Model Validation: The EGS Collab Project

Implementing enhanced geothermal systems (EGS) will require improvements in understanding stimulation of crystalline rock to create appropriate flow pathways, and the ability to effectively simulate both the stimulation and the flow and transport processes in the resulting fracture network. The US Department of Energy (DOE) is addressing these and other challenges at multiple scales. The EGS Collab project, addressed here, is performing tests and modeling at the 10 m scale. The FORGE project is performing tests at the full reservoir scale. The EGS Collab team created an underground testbed at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, at a depth of approximately 1.5 km to examine hydraulic fracturing (Experiment 1). We are currently building a second testbed at SURF at a depth of about 1.25 km aimed at investigating shear stimulation (Experiment 2). In Experiment 1, we drilled eight boreholes in a well-characterized phyllite and installed geophysical sensors in six of them to create a well-instrumented testbed to allow careful monitoring of stimulation events and flow tests. Numerical simulation was used to answer key experimental design questions, to forecast fracture propagation trajectories and extents, and to analyze and evaluate results both in near-real-time and in detailed process studies. Stimulations performed in this testbed allowed quantification of processes occurring during stimulation and the examination of dynamic flow occurrences. Long-term ambient temperature and chilled water flow tests were performed in addition to many tracer tests to examine system behavior. Our second testbed, targeted at shear stimulation, is currently being built at the SURF Facility at a depth of about 1.25 km in amphibolite under a different set of stress and fracture conditions than Experiment 1.

artificial intelligence↗

Monitoring Fracture Hydromechanical Evolution in the Lab and Field Using Unsupervised Metric Learning

Fractures evolve in time through thermal‐hydraulic‐mechanical‐chemical (THMC) processes that alter their long‐range hydraulic transport properties and modify subsurface behavior and activities. The location of subsurface fractures makes it necessary to use remote sensing techniques such as passive or active seismic monitoring for fracture characterization. In this paper, we develop a machine learning approach to monitor the evolution of fracture properties using passive seismic sources in a laboratory setting and using active seismic monitoring from the Sanford Underground Research Facility in Lead, South Dakota, at a depth of 1.25 km in amphibolite rock during stimulation of natural fractures as well as during induced fracturing. The unsupervised metric learning technique applies tandem neural networks (twin (Siamese) or triplet) with contrastive loss and adaptive margins to track slowly varying systems for which class or similarity labels are not available. The approach adopts locality‐sensitive hashing to divide time‐ordered contiguous data into an arbitrary number of pseudo‐classes. Contrastive‐loss training with many hash bins generates an evolving latent‐space trajectory. This approach enables unsupervised metric learning for seismic data stacks under the condition of contiguous state sampling and slowly varying fracture properties. The displacement discontinuity theory provides a mechanistic foundation for the fracture‐dependent trajectories that are related to relaxation of fractures with time‐dependent specific stiffness responding to changes in stress or fluid saturation.

02 PETROLEUM↗

The effects of multispecies Hohlraum walls on stimulated Brillouin scattering, Hohlraum dynamics, and beam propagation

We report experiments and simulations have been conducted to investigate the efficacy of Ta 2 O 5 -lined Hohlraum walls at reducing stimulated Brillouin backscattering (SBS) as well as any subsequent effects on the Hohlraum dynamics and capsule implosions in indirect drive experiments at the National Ignition Facility. Using a 1.1 MJ 400 TW, 351 nm, shaped laser pulse, we measure a 5× reduction in SBS power in the peak of the pulse from the wall on the outer 50° cone beams. The SBS spectrum indicates a reduction in the high-Z spectral signature when using multispecies wall materials. Detailed hydrodynamic simulations were performed using different heat conduction models with flux limiters. Additional simulations were performed on the plasma maps using the 3D parallel paraxial code pF3D to compare backscatter powers between the pure Au and Ta 2 O 5 -lined Hohlraums. Further analysis, using hydrodynamically equivalent plasmas, shows that the SBS reduction is clearly a result of the added ion Landau damping caused by the oxygen ions and not from differences in plasma conditions. The experimental and simulation results also show an increase in the wall plasma expansion when using the Ta 2 O 5 liner leading to a 70% more oblate implosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Utah FORGE 3-2418: Wellbore Fracture Imaging Using Inflow Detection - 2024 Annual Workshop Presentation

This is a presentation on the Wellbore Fracture Imaging Using Inflow Detection by Stanford University and Sandia National Laboratory, presented by Roland Horde. This is a video presentation on wells, both before and after stimulation, using chloride or other ions to map fractures and estimate their flow magnitudes. This research is being done by Stanford University. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13, 2024.

15 GEOTHERMAL ENERGY↗

Utah FORGE Well 16A(78)-32 Simplified Discrete Fracture Network Data

The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 16A(78)-32. This is a simplified DFN (discrete fracture network) dataset, that was generated using FracMan, for Utah FORGE well 16A(78)-32. A short, well-illustrated, report describing the data is also included in the provided archive file.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Reports on Northwestern Nevada Well Doublet Drilling and Testing by Fervo Energy

These reports review Fervo Energy's construction of a commercial enhanced geothermal system (EGS). Fervo has qualified full functionality of the system through production testing at commercially relevant operating conditions. The project site is located in a nearfield setting adjacent to an operating geothermal power station in north-central Nevada and is designed to deliver an uplift in high-temperature geothermal flow rates to increase the power capacity at the facility. The project involved drilling a first-of-a-kind EGS horizontal doublet well system consisting of an injection and production well pair within a high-temperature hard-rock geothermal formation. The lithology of the target reservoir is characterized as a mixed metasedimentary and igneous formation, comprised of phyllite, quartzite, diorite, and granodiorite, representative of the geology across the most prospective geothermal areas throughout the western US. This work included a 16-stage plug-and-perforate stimulation treatment which was the first of its kind in a high-temperature mixed metasedimentary and granitic formation in a fully horizontal doublet geothermal well.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗

TOUGH-RFPA: Coupled thermal-hydraulic-mechanical Rock Failure Process Analysis with application to deep geothermal wells

This paper presents a coupled thermal-hydraulic-mechanical (THM) model for simulating failure processes in geological media. The coupling between stress/strain and heat transfer describing how thermal expansion affects stress is based on the theory of thermo-elasticity. Additionally, the coupling between stress/strain and fluid flow describing how pore-pressure affects stress is governed by Biot's consolidation theory. Stress/strain-dependent porosity/permeability/capillary-pressure defines the influence of stress on fluid flow and thermal fields. The THM model is implemented in the solver module that links the multiphase, multicomponent fluid flow simulator TOUGH2 with the geomechanical simulator RFPA (Rock Failure Process Analysis), which is based on the concept that heterogeneity leads to non-linearity and progressive failure behavior. Capability of TOUGH-RFPA simulator was verified by two benchmark problems related to hydraulic-mechanical and thermal-mechanical response in a hollow cylinder. Then the applicability of TOUGH-RFPA was demonstrated for modeling cooling-induced damage around a very deep geothermal well with mesoscopic heterogeneous properties, which showed complex damage evolution and fracturing during well cooling and fluid pressurization.

42 ENGINEERING↗

Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models

This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. These models have been upscaled to a continuum mesh or grid at resolutions of 10 meters and 20 meters providing reservoir properties for fracture porosity, permeability, and compressibility. The models are available in both the reference global coordinate frame and a local coordinate frame aligned with principal stress directions.

15 GEOTHERMAL ENERGY↗

Development of fracture diagnostic methods for fluid distribution based on quantitative interpretation of distributed acoustic sensing and distributed temperature sensing

Multistage hydraulic fracturing design on horizontal wells has significantly evolved with larger fluid volume, more fracturing stages, and tighter perforation cluster spacing to efficiently stimulate unconventional reservoirs. From the published field observations, the recent fracturing design results in complex fracture networks or swarm of fractures. Fracture treatment evaluation is extremely challenging in such a case because of the large amount of variables in well completion and stimulation design. Combined measurements from different technologies can help in fracture diagnosis. Fluid distribution, either during fracture injection or during production, directly relates to the stimulation efficiency at the cluster level and at the stage level. Because it is unlikely in the real world to distribute the injected fluid uniformly among all the clusters, we need diagnostic techniques to generate the flow profile along a lateral. Fiber-optic measurements, such as distributed acoustic sensing (DAS) and distributed temperature sensing (DTS), are currently used to diagnose downhole flow conditions. This technology allows us to qualitatively confirm the fluid flow profile and other issues occurring downhole during fracturing such as leakage through plugs. For optimizing a fracturing design, we also need to understand how the design parameters are correlated with the stimulation efficiency. In this study, we combine two sets of models of DAS and DTS data interpretation for injected fluid volume distribution. The DAS is interpreted based on an empirical correlation between fluid flow rates and frequency band energy from the acoustic signals. The DTS is interpreted by performing temperature history match-based thermal energy conservation. Because of the completely different physics behind the interpretations, the confirmation of two interpretations provides confidence in fluid distribution.

Geochemistry & Geophysics↗

Geochemical reactions and alteration of pore architecture in saturated shale after injection of stimulation fluid

Pore architecture regulates fluid flow between unconventional shale reservoir and hydraulically-induced fractures. Imbibition of stimulation fluid may change this architecture and alter hydrocarbon flow. Hydrothermal experiments were conducted at reservoir conditions (125 °C, 45 MPa) to test two hypotheses: 1) Shale, not stimulation fluid, dominates the geochemistry of an unconventional reservoir containing formation water; and 2) Mineral dissolution and precipitation induced by stimulation fluid is transient and manifests across micro-, meso-, and macro-scales of pore architecture. Experiments replicated a shut-in well in the Cretaceous Baxter Shale, Green River Basin, Wyoming USA. Stimulation fluid was injected into one experiment after formation water (I = 0.35 mol/kg, pH = 6.4) and core reacted for 48 days. This novel approach equilibrated rock and formation water and saturated pores with formation water before introducing stimulation fluid. The second experiment served as a control. Trends of aqueous calcium, silica and aluminum in the injection experiment suggest transient dissolution of calcite and feldspar and/or quartz as well as clay and barite precipitation; mineralogic evidence was limited to calcite dissolution and barite precipitation. The rock maintained reducing conditions (Eh = +0.08 to -0.16 V) despite injection of oxidizing stimulation fluid (Eh = 1.1 V). pH of the stimulation fluid-formation water mixture evolved from 2.3 to pre-injection values (~6) within 24 h. The results indicate that mineral dissolution and precipitation manifest in macropores with barely detectable alteration to micro- and mesopores. Formation water or organic matter in pores may have inhibited access of stimulation fluid to micro- and mesopores

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Induced microearthquakes predict permeability creation in the brittle crust

Predicting the evolution of permeability accurately during stimulation at the reservoir scale and at the resolution of individual fractures is essential to characterize the fluid transport and the reactive/heat-transfer characteristics of reservoirs where stress exerts significant control. Here, we develop a hybrid machine learning (ML) model to visualize in situ permeability evolution for an intermediate-scale (~10 m) hydraulic stimulation experiment. This model includes an ML model that was trained using the well history of flow rate and wellhead pressure and MEQ data from the first three stimulation episodes to predict average permeability from the statistical features of the MEQs alone for later episodes. Moreover, a physics-inspired model is integrated to estimate in situ fracture permeability spatially. This method relates fracture permeability to fracture dilation and scales dilation to the equivalent MEQ magnitude, according to laboratory observations. The seismic data are then applied to define incremental changes in permeability in both space and time. Our results confirm the excellent agreement between the ground truth and model-predicted permeability evolution. The resulting permeability map defines and quantifies flow paths in the reservoir with the averaged permeability comparing favorably with the ground truth of permeability.

induced seismicity↗

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗

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.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Injection and Production Test results and Reports from August 2024

This dataset includes results and reports from the injection/production test for wells 16A(78)-32 and 16B(78)-32 in August, 2024 at Utah FORGE. Materials include injection, post stimulation production, flow rate, gamma, temperature and pressure survey results. For the respective wells, injection and production profile results and interpretations are provided in .xlsx and .las file formats. Additionally, for both wells, preliminary and final reports are included and provide logging procedures and visualizations of the results.

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↗

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.

15 GEOTHERMAL ENERGY↗

Newberry SHR Demonstration Project – Bipartisan Infrastructure Law Enhanced Geothermal (EGS) Pilot Demonstration (Abstract)

This project will create an Engineered Geothermal System (EGS) comprising two or more wells drilled to a depth of 4.25 km into superhot rock (SHR) with a temperature of 425 °C at Newberry Volcano in Central Oregon. An EGS is a manufactured heat exchanger in which water is injected in a deep injection well, or injector, to extract heat from the hot rock at depth and steam is returned to the surface in a production well, or producer, to generate electricity. In this project, the SHR EGS will be made using new methods and technologies to stimulate and connect hydraulic and natural fractures to enable multiple flow pathways between wells, allowing for optimal heat mining from the reservoir rock. The new technologies are designed to operate at rock temperatures much higher than those encountered in traditional geothermal. Following EGS completion, water will be injected into the injector well and steam extracted from the producer well in a long-term connectivity flow test demonstrating SHR reservoir evolution with time and use. Success will be measured by demonstrating the efficacy of new technologies and by producing economic quantities of steam (>40 MWth).

15 GEOTHERMAL ENERGY↗