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.
One of the greatest barriers to geothermal energy expansion is the high cost of drilling during exploration, assessment, and monitoring. Microhole drilling technology—small-diameter 2–4 in. (~5.1–10.2 cm) boreholes—is one potential low-cost alternative for monitoring and evaluating bores. However, delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes needed to realize the cost savings. Coiled tube drilling technology is one solution, but these systems are limited by the torque resistance of the coil system, helical buckling in compression, and most of all, WOB management. The evaluation presented herein will: (i) evaluate the technical and economic feasibility of low WOB technologies (specifically, a percussive hammer and a laser-mechanical system), (ii) develop downhole rotational solutions for low WOB drilling, (iii) provide specifications for a low WOB microhole drilling system, (iv) implement WOB control for low WOB drilling, and (v) evaluate and test low WOB drilling technologies.
Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. A method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improved decision-making in the field and to further discern technology performance during post-drilling evaluations. Drill rig parameter data were acquired by drilling contractor Frontier Drilling and evaluated for two wells drilled at the DOE-sponsored site, Utah Frontier Observatory for Research in Geothermal Energy (FORGE). The subject wells include: 1) FORGE 16A(78)-32, a directional well with vertical depth to a kick-off point at 5892 ft and a 65 degree tangent to a measured depth of 10987 ft and, 2) FORGE 56-32, a vertical monitoring well to a measured depth of 9145 ft. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, develop rock strength approximations, determine bit aggressiveness, characterize frictional energy losses, evaluate bit wear rates, and detect the presence of drillstring vibrations contributing to bit failure; comparisons are made to observations of bit wear and damage. Analyses are also presented to correlate performance to bit run cost drivers to provide guidance on the relative tradeoff between bit penetration rate and life. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs.
The well documented promise of microholes has not yet matched expectations. A fundamental issue is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings. Prior work has focused on miniaturizing the various systems used in conventional drilling technologies, such as motors, steering systems, mud handling and logging tools, and coiled tubing drilling units. As smaller diameters are targeted for these low WOB drilling technologies, several associated sets of challenges arise. For example, energy transfer efficiency in small diameter percussive hammers is different than conventional hammers. Finding adequate methods of generating rotation at the bit are also more difficult. A low weight-on-bit microhole drilling system was proposed, conceived, and tested on a limited scale. The utility of a microhole was quantified using flow analyses to establish bounds for usable microholes. Two low weight-on-bit rock reduction techniques were evaluated and developed, including a low technology readiness level concept in the laser-assisted mechanical drill and a modified commercial percussive hammer. Supporting equipment, including downhole rotation and a drill string twist reaction tool, were developed to enable wireline deployment of a drilling assembly. Although the various subsystems were tested and shown to work well individually in a laboratory environment, there is still room for improvement before the microhole drilling system is ready to be deployed. Ruggedizing the various components will be key, as well as having additional capacity in a conveyance system to provide additional capacity for pullback and deployment.
This report documents the key findings from the Reservoir Maintenance and Development (RM&D) Task of the U.S. Department of Energy's (DOE), Geothermal Technologies Office (GTO) Geothermal Vision Study (GeoVision Study). The GeoVision Study had the objective of conduc ting analyses of future geothermal growth based on sets of current and future geothermal technology developments. The RM&D Task is one of seven tasks within the GeoVision Study with the others being, Exploration and Confirmation, Potential to Penetration, Institutional Market Barriers, Environmental and Social Impacts, Thermal Applications, and Hybrid Systems. The full set of findings and the details of the GeoVision Study can be found in the final GeoVision Study report on the DOE-GTO website. As applied here, RM&D refers to the activities associated with developing, exploiting, and maintaining a known geothermal resource. It assumes that the site has already been vetted and that the resource has been evaluated to be of sufficient quality to move towards full-scale development. It also assumes that the resource is to be developed for power generation, as opposed to low-temperature or direct use applications. This document presents the key factors influencing RM&D from both a technological and operational standpoint and provides a baseline of its current state. It also looks forward to describe areas of research and development that must be pursued if the development geothermal energy is to reach its full potential.
Drilling is a repetitive, dangerous and costly process and a strong candidate for automation. We describe a method for autonomously controlling a rotary drilling process as it transitions through multiple materials with very different dynamics. This approach classifies the drilling medium based on real-time measurements and comparison to prior drilling data, and can identify the material type, drilling region, and approximately optimal set-point based on data from as few as one operating condition. The controller uses these set-points as initial conditions, and then conducts an optimal search to maximize performance, e.g. by minimizing mechanical specific energy. The control architecture is described, and the material estimation process is detailed. The results of experiments that implement autonomous drilling through a layered concrete and granite sample are discussed.