Geothermal energy is a sustainable and renewable energy source, which can be used in electricity production, space heating/cooling, and other industrial applications. In the recent years, it has been gathering more and more attention due to its numerous advantages as low impact on the surrounding environment, continuous power outputs, low greenhouse gas emissions, and worldwide availabilities. All make the geothermal energy a significant contributor to the global energy productions in an environmentally friendly way. One big concern of geothermal sources’ exploration is the expensive investment costs of geothermal wells. Utilizing abandoned petroleum wells for the purpose of geothermal extraction is a novel idea. Well temperature profiles help to estimate how much heat can be transferred and produced from the wells. In this paper, a literature review has been done to investigate the existing applications on geothermal energy extraction utilizing abandoned petroleum wells. Then, the case study demonstrates the importance of properties of working fluids, wellbore architecture, and operational parameters (circulation rate, inlet temperature, etc.) in geothermal energy production. The obtained results can be used to achieve an improved data interpretation and generate more optimal solutions. In geothermal projects, extensive knowledge of the heat transfer is of great importance for the economical aspect and the performance of wells. Our work demonstrates that it is a good approach to provide cost-effective solutions to enhance heat extraction from geothermal wells.

Data analytics is a process of data acquiring, transforming, interpreting, modelling, displaying and storing data with an aim of extracting useful information, so that decision-making, actions executing, events detecting and incidents managing can be handled in an efficient and certain manner. However, data analytics also meets some challenges, for instance, data corruption due to noises, time delays, missing and external disturbances, etc. This paper focuses on data quality improvement to cleanse, improve and interpret the post-well or real-time data to preserve and enhance data features, like accuracy, consistency, reliability and validity. In this study, laboratory data and field data are used to illustrate data issues and show data quality improvements with using different data processing methods. Case study clearly demonstrates that the proper data quality management process and information extraction methods are essential to carry out an intelligent digitalization in oil and gas industry.

Directional drilling is a common and essential procedure of major extended reach drilling operations. With the development of directional drilling technologies, the percentage of recoverable oil production has increased. However, its challenges, like real-time bit steering, directional drilling tools selection and control, are main barriers leading to low drilling efficiency and high nonproductive time. The fact inspires this study. Our work aims to contribute to the better understanding of directional drilling, more specifically regarding rotary steerable system (RSS) technology. For instance, finding the solutions of the technological challenges involved in RSSs, such as bit steering control, bit position calculation and bit speed estimation, is the main considerations of our study. Classical definitions from fundamental physics including Newton’s third law, beam bending analysis, bit force analysis, rate of penetration (ROP) modeling are employed to estimate bit position and then conduct RSS control to steer the bit accordingly. The results are illustrated in case study with the consideration of the 2D and 3D wellbore scenarios.

This paper presents the work that has gone into optimizing drilling performances on a laboratory-scale drilling rig, capable of drilling through rock samples in possible shortest time with preventing damages to devices for the sake of drilling costs and safety. The rig is fully functional, and we conducted successful experiments in both manual and autonomous modes. In this study, we focus on testings on drilling optimizations, failures, advancements of understanding of operational limits, and implementations of these boundaries to create a well-designed and controlled drilling rig. Case studies show that good results have been achieved in terms of optimizing drilling parameters and receiving the possible highest drilling speed when drilling different formations.

Well trajectory design and optimization are essential parts in well planning before drilling. The main objective of the design is to find an optimal trajectory for efficient and safe drilling. Meanwhile, the anticollision of well trajectory must be considered with offset wells in the same area. In general, optimal wellbore trajectory design includes some essential criteria, for example, shortest possible path, minimum tortuosity, collision avoidance, and most extended possible contact with the reservoir. This article presents a central part of plan phase represented by a trajectory planning and optimization module with a focus on anticollision design. The trajectory is optimized based either on minimization of wellbore length and dogleg severity or on the maximization of well-reservoir contact subject to strict anticollision constraint and other associated constraints or their combinations to some extent. The anticollision model considers industry standard bit error sources and their interactions and propagation along the well trajectory, and results in the separation factor as an constraint for trajectory optimization. The introduction of anticollision models to the trajectory optimization techniques has real potential in drilling design. Besides saving time and effort by providing engineers with multiple options, the well design with anticollision considerations ensures the well path safety while searching for optimal well trajectory. The presented work has a good potential in well planning as a viable method to keep drilling operations’ safe and efficient.