One of the most striking measurements taken during DOE’s EGS Collab project at the 4850-foot depth location was the so-called ‘sewer cam’, which enabled direct visualization of the flow of water into the production well through fractures during the stimulation. The ability to see directly which fractures were flowing and (roughly) how much was a breakthrough in understanding the topology of the created fracture network. Achieving this kind of fracture flow imaging at FORGE would be more challenging because of the 225°C temperature, but equally or even more valuable if it could be achieved. In 2017, a joint project between Sandia and Stanford developed a downhole tool concept to measure the enthalpy of multiphase fluid entering a geothermal well from individual fractures (Gao et al., 2017). For the FORGE project, measuring enthalpy is of less interest because the fluid is expected to be single-phase liquid water. However, the foundation of the device was the measurement of chloride ion concentration, which could form the basis for a direct measurement of inflow from fractures. During the 2017 project, this novel chloride sensing system was implemented into a laboratory test instrument, and we confirmed the capability of the system to measure the ion concentration of fluid entering a model wellbore through a small entry port. The wellbore was a 6-inch diameter model well, and the port was approximately 0.08 inch (2mm) in diameter. The device could measure the chloride concentration accurately even when the well was flowing in a bubbly flow. Given its accuracy, the tool should be able to identify locations of water entering the wellbore even if the ion concentration differs only slightly from that of the water in the well. It is likely that different fractures may flow slightly different chloride concentrations, which would make it feasible to detect individual fractures as well as to estimate the volume of their flow. Ultimately, we could also recognize different fractures flowing back significantly different ion concentrations after fracturing in the FORGE wells. This could be realized by adding different ions in the fracturing fluids in different fractures created at different stages of stimulation (and modifying the tool to include different ion specificity). Sandia’s tool was shown during the study to have the capability to withstand the 225°C temperature, and the electrochemical sensing elements were tested in the laboratory to 225°C at 1500 psia for 24 hours. An early implementation of the fully integrated downhole electrochemical tool, including high-temperature electronics, robust housing, and wireline truck interface, had previously been constructed and tested successfully at Sandia; thus, hardware development tasks focused on advancing the technology readiness level (TRL) of this promising technology for FORGE deployment, rather than on developing a new scientific basis for its operation. The data collection electronics in this tool allowed for several other sensors (pressure, temperature, flow spinner) to be implemented in parallel as well. The research was a new collaboration between Stanford and Sandia to modify and refine the tool for FORGE deployment, to make the downhole measurements, and to characterize the evolving fractures.
This paper presents the ongoing development of a chloride-based wireline tool designed to detect and quantify inflows from feed zones in geothermal wells. The tool aims to characterize stimulation events in EGS wells at Utah FORGE (Frontier Observatory for Research in Geothermal Energy) and other EGS sites. Successful development of the chloride tool would greatly improve production monitoring of the fractures and enable proactive prescription of additional stimulations over the life of the field, thus helping to improve EGS commercial feasibility. The recent developments of the chloride tool have focused on preparing for and conducting the field deployment at the Utah FORGE site. The field-scale tool assembly features a FORGE sensor package housing the Ion Selective Electrode (ISE), a pH electrode, and a reference electrode, as well as a Mitco PTS sensor package for secondary downhole measurements. A high-temperature logging tool has been developed and tested to capture and transmit data from the chemical sensors to the surface through a 7-conductor wireline cable. Alongside the development of the field-scale tool, flow experiments were carried out in the artificial well system at the Stanford Geothermal Lab. These experiments provided crucial insights into how the chemical tool responds to different variables, including the chloride concentration in the feed zone, its vertical positioning relative to the feed zone, and the presence of other chemical species in the feed zone fluid. The results highlight the tool's sensitivity to various parameters, underscoring the potential of using chloride concentration measurements as a method for inferring feed zone inflow rates in geothermal wells. The tool was successfully deployed at the Utah FORGE site using a wireline truck in the vertical well 58-32 and the directional production well 16B(78)-32.
Achieving robust and efficient drilling is a critical part of reducing the cost of geothermal energy exploration and extraction. Drilling performance is often evaluated using one or more of three key metrics: depth of cut (DOC), rate of penetration (ROP), and mechanical specific energy (MSE). All three of these quantities are related to each other. DOC refers to the depth a bit penetrates into rock during drilling. This is an important quantity for estimating bit behavior. ROP is the simply the DOC multiplied by the rotational rate, and represents how quickly the drill bit is advancing through the ground. ROP is often the parameter used for drilling control and optimization. Finally, MSE provides insight into drilling efficiency and rock type. MSE calculations rely on ROP, drilling force, and drilling torque. Surface-based sensors at the top of the drill are often used to measure all these quantities. However, top-hole measurements can deviate substantially from the behavior at the bit due to lag, vibrations, and friction. Therefore, relying only on top-hole information can lead to suboptimal drilling control. In this work, we describe recent progress towards estimating ROP, DOC, and MSE using down-hole sensing. We assume down-hole measurements of torque, weight-on-bit (WOB). Our hypothesis is that these measurements can provide more rapid and accurate measures of drilling performance. We show how a multi-layer perceptron (MLP) machine learning algorithm can provide rapid and accurate performance when evaluated on experimental data taken from Sandia’s Hard Rock Drilling Facility. In addition, we implement our algorithms on an embedded system intended to emulate a bottom-hole-assembly for sensing and estimation. Our experimental results show that DOC can be estimated accurately and in real-time. These estimates when combined with measurements for rotary speed, torque, and force can provide improved estimates for ROP and MSE. These results have the potential to enable better drilling assessment, improved control, and extended component lifetimes.
This report captures the results of development and testing of a integral downhole motor and percussive hammer used for drilling in near-surface hard rock formations. The work was funded through the DOE Office of Technology Transitions Technology Commercialization Fund. It was a collaboration between Sandia National Labs and The Charles Machine Works (aka Ditch Witch). In the collaboration, Sandia developed a pneumatic motor derived from an indexing tool used in other drilling applications, and Ditch Witch developed the bearing pack tied to the output shaft of the motor as well as the angled beacon housing used for directional control.
Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO2—creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.
Sausan, Sarah; Judawisastra, Luthfan H.; Su, Jiann-Cherng; Horne, Roland
This paper presents the ongoing development of a wireline tool designed to detect and quantify inflows from feed zones in geothermal wells based on measurement of chloride. The tool aims to characterize stimulation events in Enhanced Geothermal Systems (EGS) wells at Utah FORGE (Frontier Observatory for Research in Geothermal Energy) and other EGS sites. Successful development of the chloride tool would greatly improve production monitoring of the fractures and enable proactive prescription of additional stimulations over the life of the field, thus helping to improve EGS commercial feasibility. The recent development of the chloride tool involves an Ion Specific Electrodes (ISE) probe and a reference electrode, assembled through a labor-intensive process, and designed to withstand downhole conditions for field deployment. Through laboratory experiments and numerical simulations, the tool demonstrated efficacy in identifying changes in chloride concentration, indicating its utility in feed zone detection. However, the impact of impedance on voltage measurements and discrepancies between laboratory and simulation results presented opportunities for further refinement. Notably, simulation results consistently underestimated actual chloride concentration by 30-40%, suggesting the need for compensatory calibration. Comparisons between different simulation software indicated that ANSYS was more accurate in replicating key features observed in laboratory experiments. Moreover, a Machine Learning (ML) approach was used to improve feed zone location detection and inflow rate measurement, utilizing Random Forest and Light Gradient Boosting Machine (LGBM) models, which delivered high performance scores. Thus, the chloride tool's recent development and integration with machine learning approaches offer promising advancements in feed zone identification and quantification.
Robertson, Michelle; Su, Jiann-Cherng; Kaven, J.O.; Hopp, Chet; Hirakawa, Evan; Gasperikova, Erika; Dobson, Patrick; Schwering, Paul C.; Nakata, Nori; Majer, Ernest L.
The DOE GeoVision study identified that Enhanced Geothermal Systems (EGS) resources have the potential to provide a significant contribution toward achieving the goal of converting the U.S. electricity system to 100% clean energy over the next few decades. To further the implementation of commercial EGS development, DOE's Geothermal Technologies Office (GTO) initiated the Wells of Opportunity (WOO) Amplify program, where unproductive wells in selected geothermal fields are to be stimulated using EGS technologies, resulting in increased power production from these resources. As part of the WOO-Amplify project, GTO assembled the Amplify Monitoring Team (AMT), whose role is to provide in-field and near-field seismic monitoring design, deployment and data analysis for stimulations under the WOO-Amplify initiative. This team, consisting of scientists and engineers from Lawrence Berkeley National Laboratory (LBNL), Sandia National Laboratories (SNL), and the US Geological Survey (USGS), is working with WOO-Amplify EGS Operators in Nevada to develop and deploy optimized seismic monitoring systems at four geothermal fields where WOO-Amplify well stimulations are planned: Don A. Campbell, Tungsten Mountain and Jersey Valley operated by Ormat Technologies, and Patua operated by Cyrq Patua Acquisition Company LLC. Using geologic and geophysical field data provided by the WOO-Amplify teams, the focus of the AMT is to develop advanced simulation and modeling techniques, design targeted seismic monitoring arrays, develop innovative and cost-effective methodologies for drilling seismic monitoring boreholes, deploy effective seismic instrumentation, and facilitate the use of microseismic data to monitor well stimulation and flow within the geothermal reservoir. Realtime seismic data from the four WOO-Amplify sites will be streamed to a publicly accessible Amplify Monitoring website. AMT's advanced simulations and template matching techniques applied during pre-stimulation phases can help improve understanding of potential seismic hazard and inform the Operator's Induced Seismicity Mitigation Protocol (ISMP). Over the next two years, AMT will be drilling, instrumenting, and recording seismic data at the WOO-Amplify field sites, telemetering the seismic waveform data to AMT's central processing system and providing the processed location data to the WOO Amplify Operator teams. These data and monitoring systems will be critical for effective monitoring of the effects of planned well stimulation and extended flow tests during the next stage of the WOO-Amplify project.
Geothermal energy has been underutilized in the U.S., primarily due to the high cost of drilling in the harsh environments encountered during the development of geothermal resources. Drilling depths can approach 5,000 m with temperatures reaching 170 C. In situ geothermal fluids are up to ten times more saline than seawater and highly corrosive, and hard rock formations often exceed 240 MPa compressive strength. This combination of extreme conditions pushes the limits of most conventional drilling equipment. Furthermore, enhanced geothermal systems are expected to reach depths of 10,000 m and temperatures more than 300 °C. To address these drilling challenges, Sandia developed a proof-of-concept tool called the auto indexer under an annual operating plan task funded by the Geothermal Technologies Program (GTP) of the U.S. Department of Energy Geothermal Technologies Office. The auto indexer is a relatively simple, elastomer-free motor that was shown previously to be compatible with pneumatic hammers in bench-top testing. Pneumatic hammers can improve penetration rates and potentially reduce drilling costs when deployed in appropriate conditions. The current effort, also funded by DOE GTP, increased the technology readiness level of the auto indexer, producing a scaled prototype for drilling larger diameter boreholes using pneumatic hammers. The results presented herein include design details, modeling and simulation results, and testing results, as well as background on percussive hammers and downhole rotation.
Drilling systems that use downhole rotation must react torque either through the drill-string or near the motor to achieve effective drilling performance. Problems with drill-string loading such as buckling, friction, and twist become more severe as hole diameter decreases. Therefore, for small holes, reacting torque downhole without interfering with the application of weight-on-bit, is preferred. In this paper, we present a novel mechanism that enables effective and controllable downhole weight on bit transmission and torque reaction. This scalable design achieves its unique performance through four key features: (1) mechanical advantage based on geometry, (2) direction dependent behavior using rolling and sliding contact, (3) modular scalability by combining modules in series, and (4) torque reaction and weight on bit that are proportional to applied axial force. As a result, simple mechanical devices can be used to react large torques while allowing controlled force to be transmitted to the drill bit. We outline our design, provide theoretical predictions of performance, and validate the results using full-scale testing. The experimental results include laboratory studies as well as limited field testing using a percussive hammer. These results demonstrate effective torque reaction, axial force transmission, favorable scaling with multiple modules, and predictable performance that is proportional to applied force.
Wellbore integrity is a significant problem in the U.S. and worldwide, which has serious adverse environmental and energy security consequences. Wells are constructed with a cement barrier designed to last about 50 years. Indirect measurements and models are commonly used to identify wellbore damage and leakage, often producing subjective and even erroneous results. The research presented herein focuses on new technologies to improve monitoring and detection of wellbore failures (leaks) by developing a multi-step machine learning approach to localize two types of thermal defects within a wellbore model, a prototype mechatronic system for automatically drilling small diameter holes of arbitrary depth to monitor the integrity of oil and gas wells in situ, and benchtop testing and analyses to support the development of an autonomous real-time diagnostic tool to enable sensor emplacement for monitoring wellbore integrity. Each technology was supported by experimental results. This research has provided tools to aid in the detection of wellbore leaks and significantly enhanced our understanding of the interaction between small-hole drilling and wellbore materials.
