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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Corrigendum to "Environmentally friendly, rheoreversible, hydraulic fracturing fluids for enhanced geothermal systems" [Geothermics 58 (2015) 22–31]

Cost-effective creation of high-permeability reservoirs inside deep crystalline bedrock is the primary challenge for the feasibility of enhanced geothermal systems (EGS). Current reservoir stimulation entails adverse environmental impacts and substantial economic costs due to the utilization of large volumes of water “doped” with chemicals including rheology modifiers, scale and corrosion inhibitors, biocides, friction reducers among others where, typically, little or no information of composition and toxicity is disclosed. An environmentally benign, CO2-activated, rheoreversible fracturing fluid has recently been developed that significantly enhances rock permeability at effective stress significantly lower than current technology. We evaluate the potential of this novel fracturing fluid for application on geothermal sites under different chemical and geomechanical conditions, by performing laboratory-scale fracturing experiments with different rock sources under different confining pressures, temperatures, and pH environments. The results demonstrate that CO2-reactive aqueous solutions of environmentally amenable Polyallylamine (PAA) represent a highly versatile fracturing fluid technology. This fracturing fluid creates/propagates fracture networks through highly impermeable crystalline rock at significantly lower effective stress as compared to control experiments where no PAA was present, and permeability enhancement was significantly increased for PAA compared to conventional hydraulic fracturing controls. This was evident in all experiments, including variable rock source/type, operation pressure and temperature (over the entire range for EGS applications), as well as over a wide range of formation-water pH values. This versatile novel fracturing fluid technology represents a great alternative to industrially available fracturing fluids for cost-effective and competitive geothermal energy production.

Shao, Hongbo↗
DOE OSTI2016

The Application of Hydraulic and Thermal Stimulation Techniques to Create Enhanced Geothermal Systems

Geothermal energy production requires temperature at depth, a working fluid to transport heat to the surface, and a network of fluid pathways connecting injection and production wells. These requirements constrain the availability of geothermal energy resources. Enhanced Geothermal System (EGS) development expands geothermal resource availability by artificially generating networks of fluid pathways in the reservoir. This is accomplished through hydraulic and thermal stimulation of the geothermal reservoir. Hydraulic and thermal techniques were applied at the Raft River geothermal field as part of a Department of Energy (DOE) EGS development project. The test well RRG-9 ST1 was hydraulically stimulated three times between February 2012 and April 2014. Since June, 2013 continuous injection of sub-reservoir temperature plant water has been used to thermally stimulate the well. The stimulation program has resulted in a large increase in the injectivity of the well, an increase from less than 20 gpm in June 2013 to nearly 1,000 gpm in April 2016. Wellbore imaging and temperature analysis identified a northeast striking fracture zone intersecting the well between 5,640 and 5,660 ft. measured depth (MD) has nominally accepted all of the injected fluid. Microseismic activity, related to stimulation program and plant activity was used to track possible fluid pathways within the reservoir. The microseismic data indicates that the injected fluid moves primarily to the northeast through the Narrows Zone, a northeast striking fault structure that bisects the field. Tracers injected into RRG-9 ST1 and recovered at the production wells RRG-2 and RRG-4, located to the northeast of RRG-9 ST1, support this theory. It is hypothesized that water injected into RRG-9 ST1 moves through the intersecting fracture zone which connects into the Narrows Zone, and then moves along the Narrows Zone to the northeast. This conceptual model was numerical simulated using FALCON a finite element reservoir simulation code developed by Idaho National Laboratory. The modeling suggests that both thermal and hydraulic fracturing mechanisms played an important role in improving the injectivity at RRG-9 ST1. The stimulation program at Raft River has successfully demonstrated the effectiveness of hydraulic and thermal stimulation techniques. RRG-9 ST1 is now in commercial use.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

A suite of benchmark and challenge problems for enhanced geothermal systems

A diverse suite of numerical simulators is currently being applied to predict or understand the performance of enhanced geothermal systems (EGS). To build confidence and identify critical development needs for these analytical tools, the United States Department of Energy, Geothermal Technologies Office sponsored a Code Comparison Study (GTO-CCS), with participants from universities, industry, and national laboratories. A principal objective for the study was to create a community forum for improvement and verification of numerical simulators for EGS modeling. Teams participating in the study were those representing U.S. national laboratories, universities, and industries, and each team brought unique numerical simulation capabilities to bear on the problems. Two classes of problems were developed during the study, benchmark problems and challenge problems. The benchmark problems were structured to test the ability of the collection of numerical simulators to solve various combinations of coupled thermal, hydrologic, geomechanical, and geochemical processes. This class of problems was strictly defined in terms of properties, driving forces, initial conditions, and boundary conditions. The challenge problems were based on the enhanced geothermal systems research conducted at Fenton Hill, near Los Alamos, New Mexico, between 1974 and 1995. The problems involved two phases of research, stimulation, development, and circulation in two separate reservoirs. The challenge problems had specific questions to be answered via numerical simulation in three topical areas: (1) reservoir creation/stimulation, (2) reactive and passive transport, and (3) thermal recovery. Whereas the benchmark class of problems were designed to test capabilities for modeling coupled processes under strictly specified conditions, the stated objective for the challenge class of problems was to demonstrate what new understanding of the Fenton Hill experiments could be realized via the application of modern numerical simulation tools by recognized expert practitioners. Lastly, we present the suite of benchmark and challenge problems developed for the GTO-CCS, providing problem descriptions and sample solutions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗
DOE OSTI2026

Stochastic fracture generation and thermo-hydro-mechanical modeling in an equivalent continuum framework for enhanced geothermal systems

Enhanced geothermal systems (EGS) involve fracturing low permeability material to establish well connectivity and then injecting and circulating fluid into the fractured subsurface for geothermal power production. Changes in fracture aperture from contraction of the cooling matrix rock may alter network connectivity and risk thermal short-circuiting. Thermo-hydro-mechanical (THM) models are a useful tool to study these processes. However, as fracture networks are complex, and data may be limited, fracture networks in THM models are often stochastically generated. Given reliance on stochastic fracture networks and THM modeling to represent the subsurface and assess productivity of EGS, increased understanding of the influence of such statistically derived fracture networks on flow and heat transport in THM models is needed. Here, a new fracture process model is developed in the reactive transport code PFLOTRAN to stochastically generate fracture families and simulate changes in fracture aperture over time due to temperature changes of the rock matrix. Sixty-four different fracture networks ranging from well to poorly-connected, are modeled in PFLOTRAN with and without mechanical processes (THM vs TH). Results indicate that for well-connected fracture networks, thermal short-circuiting is less of a concern due to the abundance of available alternative flowpaths. For poorly-connected fracture networks, inclusion of mechanical processes showed steep thermal drawdown coincident with increase in fracture aperture along developing colder flowpaths, demonstrating the risk of thermal short-circuiting. Simulations with additional, larger fractures engineered to establish connectivity in a poorly-fractured subsurface, indicate that while stochastic variation of fracture orientation of the background network had limited influence, such variation in the engineered fractures significantly affected flow and heat transport.

Discrete fracture networks (DFN)↗
DOE OSTI2021

Modeling heat transport processes in enhanced geothermal systems: Validation study from EGS Collab Experiment 1

Heat recovery from enhanced geothermal systems (EGS) is a complex process involving heat transport in both fracture networks and rock formations. A comprehensive understanding of and the ability to model the underlying heat transport mechanisms is important for the success of EGS but remains challenging in practice due to the generally insufficient characterization of EGS reservoirs. In the present study, we analyze an extensively monitored intermediate-scale EGS field experiment performed in a well-characterized testbed. The high-resolution, high-quality measurements from the field experiment enable the development of a high-fidelity model incorporating a well-constrained fracture network. Based on the field experiment, we investigate the complex heat transport processes in an EGS-relevant environment and validate the capability of a numerical approach in simulating these inherently coupled heat transport processes. A series of numerical simulations were performed to study the effects of different heat transport mechanisms, including thermal convection with fracture flow, thermal conduction in rock formations, and the Joule-Thomson effect. The agreement of thermal responses between field measurements and simulation results indicates that our numerical approach can appropriately model the heat transport processes pertaining to heat recovery from EGS reservoirs.

Wu, Hui↗
DOE OSTI2023

Deep Learning for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting cold water into a subsurface fractures, which are in contact with the hot dry rock, and pulled through the production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. To develop economically viable EGS reservoirs, significant technical barriers (e.g., better stimulation technologies without adequate water and/or permeability) and non-technical barriers (e.g., land access and permitting) must be overcome. In this short conference paper, we present a workflow to address a part of this challenge – “How to develop economically viable EGS using existing technologies?”. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and cloud computing. This GTC framework is open-source and available at https://github.com/SmartTensors/GeoThermalCloud.jl. The GTC framework provides trained deep learning (DL) models to estimate the net present value of a given EGS design scenario. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. The database consists of EGS design parameters (inputs to DL model) and their net present value (output of DL model) in uncertain geologic systems. The EGS design parameters for constructing this training database are based on Utah FORGE but include the options of more wells and deeper depths. The DL models are trained by ingesting the EGS design parameters and estimating the corresponding net present value. Such an emulation allows us to screen various EGS designs quickly and identify good development strategies by coupling them with optimization techniques. Our preliminary results show promise in DL emulation of net present value. However, a lot more work is needed to improve the predictive capability of DL models (i.e., extensive hyperparameter tuning is necessary). This will be the primary focus of our future work.

artificial neural networks, geothermal↗
DOE OSTI2023

GeoThermalCloud for EGS – An Open-source, User-friendly, Scalable AI Workflow for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting relatively cold water into subsurface fractures, which are in contact with hot dry rock, and brought back to surface through production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. In this short conference paper, we present a reproducible workflow for modeling EGS. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and high-performance computing. This GTC framework is currently being made open-source, user-friendly, and reproducible through python scripts as well as Google Colab/Jupyter Notebooks. This GTC for EGS modeling scripts are made available at https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS and will constantly be updated to cater for geothermal community. Current GTC framework provides scripts to train deep learning (DL) models for techno-economics and data worth analysis. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. This short paper provides details on the scripts to curate, process, and train DL models. The scripts can easily be modified to train on databases generated by other popular open-source simulators such as PFLOTRAN, STOMP, TOUGH, and GEOSX or commercial software such as ResFrac and COMSOL.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Coupled Thermo–Hydro–Mechanical Modeling of Hydro-Shearing Stimulation in an Enhanced Geothermal System in the Raft River Geothermal Field, USA

The Raft River Enhanced Geothermal System (EGS) demonstration project aims to improve the geothermal production by enhancing the reservoir permeability via shear stimulation in well RRG-9. In this paper, we performed a series of 3D thermo– hydro–mechanical (THM) simulations to investigate the influence of hydraulic and thermal effects on the development of this EGS. The model includes synthetic fracture populations based on borehole televiewer images and in-situ stress measurements from well RRG-9. Fracture permeability evolution is determined using an empirical permeability law developed from laboratory experiments. The model was calibrated by comparing the hydraulic response to field observations, including wellhead pressure, injection rate, and well injectivity. Particularly, we analyzed the enhancement of reservoir permeability and the spatial extent of the stimulation zone for the given injection schedule. Our results indicate that the permeability enhancement of fractured geothermal reservoir is caused by the combined effects of injection-induced cooling and fluid pressure increase. The decrease of temperature plays a dominant role in reactivation of natural fractures under the hydro-shearing mechanism, while the higher injection pressure promotes shear failure and enlarges the stimulation zone. Finally, for the specified extensional stress state, the model favors greatest permeability enhancement along the maximum horizontal principal stress, a moderate vertical enhancement, and a smaller gain along the minimum horizontal principal stress.

58 GEOSCIENCES↗
DOE OSTI2018

Analysis of seismic moment tensors and in situ stress during Enhanced Geothermal System development at The Geysers geothermal field, California

Seismicity in the vicinity of an Enhanced Geothermal System (EGS) demonstration project in the Northwest Geysers at the Prati 32 (P-32) injection well and the Prati State 31 (PS-31) production well is investigated to determine earthquake focal mechanisms, moment magnitudes and in situ stress of events that occur before and during reservoir stimulation starting 2011 October 6. We present a catalogue of 167 waveform-based seismic moment tensors ranging in moment magnitude from 0.6 to 3.9. The moment tensor catalogue is subsequently used to invert for the stress tensor and to investigate possible temporal stress changes resulting from fluid injection. We find an approximate 15-degree counter-clockwise rotation of the least compressive stress σ3 during injection. More remarkable is a change in orientation of the maximum compressive stress σ1 from subhorizontal to vertical when injection operations temporarily cease. The orientation of σ1 returns to subhorizontal when injection operations resume. It is found that there was a systematic reduction in the stress shape factor, R, as the injected water volume increases, indicating an evolution towards a more transtensional stress state.

58 GEOSCIENCES↗
DOE OSTI2024

Machine Learning‐Assisted Microearthquake Location Workflow for Monitoring the Newberry Enhanced Geothermal System

Abstract Enhanced geothermal systems (EGS) offer a sustainable energy source but face challenges in accurately locating microearthquakes induced during reservoir stimulation. Locating these microearthquakes provides reliable feedback on the stimulation progress. Current deep learning methods for locating earthquakes require extensive data sets for training, which is problematic as detected microearthquakes are often limited. To address the scarcity of training data, we propose a practical workflow using probabilistic multilayer perceptron (PMLP) which predicts microearthquake locations from cross‐correlation time lags in waveforms. Utilizing a 3D velocity model of Newberry site derived from ambient noise interferometry, we generate numerous synthetic microearthquakes and 3D acoustic waveforms for PMLP training. Accurate synthetic tests prompt us to apply the trained network to the 2012 and 2014 stimulation field waveforms. To enhance the accuracy of source localization, we carefully handpick the P‐arrival times. Predictions on the 2012 stimulation data set show major microseismic activity at depths of 0.5–1.2 km, correlating with a known casing leakage scenario. In the 2014 data set, the majority of predictions concentrate at 2.0–2.9 km depths, consistent with results obtained from conventional physics‐based inversion, and align with the presence of natural fractures from 2.0 to 2.7 km. We validate our findings by comparing the synthetic and field picks, demonstrating a satisfactory match for the first arrivals. By combining the benefits of quick inference speeds and accurate location predictions, we demonstrate the feasibility of using realistic synthetic data set to locate microseismicity for EGS monitoring.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

High Temperature Stability of Aqueous Foams for Potential Application in Enhanced Geothermal System (EGS)

Enhanced Geothermal Systems (EGS) are typically constructed by injecting high-pressure water into the deep hot dry rocks (HDR) under carefully controlled conditions to create new or re-open existing fractures, which usually utilizes an immense quantity of water. Alternatively, aqueous foam-based fracturing fluids may offer potential advantages over conventional water-based fracturing fluid, including reduced consumption of water and environmental impact. Although foam-based fracturing has shown promising results in oil and gas industries, its applicability to EGS is unknown. Foams are complex mixtures of liquids with gaseous phases that are thermodynamically unstable. Their stability will decrease over time due to liquid drainage, bubble coarsening, and coalescence. Therefore, it is essential to stabilize foam fluids at high temperatures for EGS related applications such as fracking of HDRs.This paper is focused on investigating high-temperature stability of N2-in-water or N2 foams containing different surfactants and stabilizing agents. Foam stability was characterized by the half-life, which is defined as the time a foam decreases to 50% of its original height due to drainage. Surfactants with various concentrations dissolved in deionized water were investigated, including alfa olefin sulfonate (AOS), sodium dodecyl sulfonate (SDS), TergitolTM (NP – 40), and cetyltrimethylammonium chloride (CTAC). Also, the effects of other stabilizing agents, including guar gum, bentonite clay, crosslinker, graphene oxide (GO) dispersion on foam stability were tested. Initial results showed that foam stability decreased dramatically as temperature increased. On the other hand, foams became relatively more stable as pressure increased. Certain stabilizing agents, such as guar gum and crosslinker, can enhance foam stability at a wide range of temperatures. Our results indicate that it may be possible to obtain stable foams at high-temperature, high-pressure conditions with appropriate stabilizing agents.

Thakore, Virensinh↗
DOE OSTI2022

High Temperature, High Pressure Stability of Aqueous Foams for Potential Application in Enhanced Geothermal System (EGS)

Enhanced Geothermal Systems (EGS) are typically constructed by injecting high-pressure water into deep hot dry rocks (HDR) under carefully controlled conditions to create new or re-open existing fractures, which usually uses an immense quantity of water. In lieu, a more sustainable technique is to utilize aqueous foams as fracturing fluid to reduce water consumption and waste-water treatments of conventional hydraulic fracturing. Although foam-based fracturing has shown promising results in oil and gas industries, its feasibility is not demonstrated in EGS conditions that usually involve high temperature and high pressures. One potential barrier of utilizing foams in EGS applications is that foams are thermodynamically unstable and will become more unstable with increasing temperature due to liquid drainage, bubble coarsening, and coalescence. This work focuses on evaluation of the stability of selected aqueous foams under high-temperature and high-pressure conditions. Specifically, foams generated with surfactant alfa olefin sulfonate (AOS) were studied at temperature up to 200oC, while the pressure ranged between 100 psi and 1000 psi. The effect of additional stabilizing agents was also examined, including guar gum, bentonite clay, borate salt crosslinker, silicon dioxide nanoparticles (SiO2), and graphene oxide (GO) dispersion. Results showed that the stabilizing agents can enhance the foam thermal stability. Foams made with AOS and the borate salt crosslinker exhibited the longest half-life of 20 min at 200°C when the pressure was at 1000 psi. Data fitting showed that foam stability decreased exponentially as temperature increased. On the other hand, pressure increased the foam half-life which followed a power model. This study indicates that it may be possible to obtain highly stable foams at high-temperature and high-pressure conditions with appropriate stabilizing agents.

Thakore, Viren↗