Geothermal Drilling and Completions: Petroleum Practices Technology Transfer

Snyder, Neil; Visser, Charles; Alfred, Eustes Iii W; Baker, Walt; Tucker, J.; Quick, Ralph; Nagle, Taylor; Bell, Jason; Bell, Sean; Bolton, Daniel; Nagandran, Uneshddarann

doi:10.2172/1490999

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Research indicates that greater than 10% of the typical drilling expenses are accumulated from the lost circulation difficulties (Kiran and Salehi, 2020). Snyder et al (2019) recommended that around 90% of the circulation is lost in well drilling described for the non-beneficial period in the extended segment of geothermal drilling.…”

Section: Introductionmentioning

confidence: 99%

Integrated approach using petrophysical, gravity, and magnetic data to evaluate the geothermal resources at the Rahat Volcanic Field, Saudi Arabia

et al. 2023

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It is necessary to develop and explore geothermal resources to achieve sustainable development and clean renewable energy around the Globe. Geothermal energy is crucial to the future energy supply to meet the environmentally friendly energy demand of the World. The Rahat Volcanic Field (Kingdom of Saudi Arabia) is the oldest and lengthiest Cenozoic Volcanic Field in the World. It is a dominantly a mature mafic Volcanic Field that holds three major geological events; the historic eruption (1256 C.E.), the five fingers (∼4500–1500 BP), and the seismic swarm (1999 C.E.). These incidents were studied by utilizing geological information and geophysical data sets. Geophysical and geostatistical research includes gravity and magnetic survey data, including different log curves and major elements, obtained from water samples as well as of volcanic rocks obtained by X-ray fluorescence (XRF). To gain an understanding of the subsurface thermal structure, these datasets were analyzed. The primary goal of this study is to identify the prominent potential geothermal resources with the help of an available data set. Findings suggest that beneath the historic eruption site along with the fissure eruption, on the western side, there is a geothermal anomaly with a surface footprint of about 35 km2. Analyzing gravity and magnetic data as well as density and magnetic susceptibility variations in rock samples led to the mapping of this anomaly. It has been inferred through integrated study that statistical analysis of major elements will be helpful to validate the results of the outcome.

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Section: Introductionmentioning

confidence: 99%

Integrated approach using petrophysical, gravity, and magnetic data to evaluate the geothermal resources at the Rahat Volcanic Field, Saudi Arabia

et al. 2023

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Machine Learning Based Intelligent Downhole Drilling Optimization System Using An Electromagnetic Short Hop Bit Dynamic Measurements

Losoya

Vishnumolakala

Gildin

et al. 2020

SPE Annual Technical Conference and Exhibition

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The primary objective of this research is to develop an advanced real-time advisory system to help drillers make more effective decisions and optimize Rate of Penetration (ROP), thereby improving overall drilling performance. Transformational digital technologies such as distributed processing and machine learning techniques have been utilized in developing the ‘brains' of the system. This, combined with robust electronics and high-speed short-hop electromagnetic (EM) telemetry system, enables the development of a downhole drilling optimization system. A finite element model based on the concept of ‘transfer impedance’ was implemented in MATLAB to develop the Earth/Drillstring (E/D) model, which was used for validating the short-hop module prototype before performing field tests. With high-speed telemetry and processor downhole, the system has the capability to process and analyze raw sensor signals at the bit, improving the data transmission rate, actuation delay, and response time. Successful Machine Learning models were determined by ensemble learning of multiple classifiers that are trained and tested on real-world drilling data. Four dysfunction types are targeted in this study - Whirl, Stick-slip, Axial vibrations & Lateral vibrations. The limitation of current drilling advisory systems in the industry is that they rely mostly on rig instrumentation data available at the surface due to lack of a reliable, consistent, and, more importantly, cost-effective downhole telemetry system that can offer high-speed and high bandwidth. Our main contribution to overcome this limitation results from the fact that we are processing the high-frequency data downhole at the bit utilizing advanced pre-trained machine learning models to identify drilling dysfunctions in real-time. The output of the models is transmitted using a state-of-the-art high-speed EM telemetry system, facilitating a real-time advisory system for drillers at the surface. Drilling data from several wells were used to train the models using classification algorithms - Logistic Regression, KNN, Decision Trees, Random Forest, Artificial Neural Networks, and Naive-Bayes classifiers. More than 30 parameters were used in the models with Weight-on-Bit, RPM, Torque, Mechanical Specific Energy playing a major role. Results from each of the classifiers are compared for accuracy and complexity. The highest accuracy of 89% was achieved in successfully identifying dysfunctions downhole when tested on real-world data. A library of bit dysfunction conditions and corresponding corrective actions for Whirl, Stick-slip, Axial vibrations & Lateral vibrations were developed using a hybrid of data-driven and physics-based techniques. In this paper, we introduce a novel technique to overcome two main constraints - speed and bandwidth, faced by most drilling optimization systems. A short-hop EM telemetry system ensures high-speed downhole-surface communication links, and an advanced processor with bit dysfunction libraries eliminates the need for high bandwidth. Design of the telemetry system, simulated models, and machine learning algorithms presented in the paper aid in developing a highly cost-effective intelligent drilling advisory system, which can lead to improvements in safety and non-productive time of drilling operations.

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Geothermal Drilling and Completions: Petroleum Practices Technology Transfer

Abstract: Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free via www.OSTI.gov.

Cited by 2 publications

References 4 publications

Integrated approach using petrophysical, gravity, and magnetic data to evaluate the geothermal resources at the Rahat Volcanic Field, Saudi Arabia

Integrated approach using petrophysical, gravity, and magnetic data to evaluate the geothermal resources at the Rahat Volcanic Field, Saudi Arabia

Machine Learning Based Intelligent Downhole Drilling Optimization System Using An Electromagnetic Short Hop Bit Dynamic Measurements

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