drilling engineer

Best Approach From Drilling Perspective Through Concept Select to Pre-FEED for Long Term Development of Offshore Brown Oil Field in Middle East Area

Fujinaga, Ryota (ADNOC Offshore, Abu Dhabi, UAE) | Toki, Takahiro (ADNOC Offshore, Abu Dhabi, UAE) | Toma, Motohiro (ADNOC Offshore, Abu Dhabi, UAE) | Andrews, Kerron Kerman (ADNOC Offshore, Abu Dhabi, UAE) | Alloghani, Khalid Hussain (ADNOC Offshore, Abu Dhabi, UAE)

OnePetroMay, 2023

Abstract Concept Select and Preliminary Front End Engineering and Design (Pre-FEED) were carried out on a long-term development plan (LTDP) for a brown oil field with nearly 200 existing Wellhead Towers (WHTs) and four existing artificial islands in the middle east area. The development objective is ramping up the production to certain rate and sustain it as long as economically feasible. This paper will describe: Critical stuff that needs to be performed or taken into account from drilling perspective during Concept Select/Design and Pre-FEED How the drilling discipline should be proactively engaged through Concept Select and Pre-FEED for development project of offshore brown oil field During the Concept Select, necessary data related to drilling was firstly collected such as well target locations, available slots on existing WHTs etc. In addition to that, several assumptions were set, associated with drilling rig specifications, constraints on drilling feasibility and number of well slots on new WHT. Based on the data and assumptions, multiple concepts were developed with respect to different drill centers including new WHTs, new artificial islands and existing WHTs/islands in coordination with other disciplines. Techno-economical evaluation was conducted on each concept. Subsequently, Pre-FEED was conducted based on the selected concept. During the Pre-FEED, more detailed study on WHT locations, WHT orientations, WHT design, island location, island design, HSE assessment etc. was conducted by Pre-FEED contractor, incorporating basis and requirements from all the concerned disciplines. Through the Concept Select and Pre-FEED for Long Term Development Plan (LTDP), following things were found important: Generic drilling limits like maximum horizontal departure to targets should be defined clearly at early timing of Concept Select for optimization of well allocation to drill centers Rig specifications and its limits like air gap, skidding envelope and allowable drilling load should be identified at early stage for optimization of WHT design/locations and island design Slot-to-slot distance and row-to-row distance are quite important especially for island in terms of rig operability on island and anti-collision between wells Requirements for area and its arrangement on island should be well defined item-by-item to avoid shortage in the area dedicated for drilling during subsequent stage of project Anything that needs to be studied or considered by Front End Engineering and Design (FEED) contractor should be captured in FEED Scope of Work (SoW) with detailed requirements, which will be utilized for tender process. Anything that is not captured in the FEED SoW could result in variation order or be difficult to be added to the scope after contract award. This paper will present not only the experience in this specific project but also a fundamental approach that will be applicable in any other offshore brown oil fields worldwide.

OnePetro

doi: 10.2118/214610-MS

SPE

SPE-214610-MS

SPE/IADC Middle East Drilling Technology Conference and Exhibition

Country:

North America > United States > Texas > Terry County (1.00)
North America > United States > Texas > Gaines County (1.00)
Europe > United Kingdom > North Sea > Southern North Sea (1.00)
Asia > Middle East > UAE > Abu Dhabi > Abu Dhabi (0.16)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Drilling > Drilling Operations > Drilling operation management (0.48)
Management > Strategic Planning and Management > Project management (0.47)

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Abstract In the past decade, the operators and service companies are seeking an integration solution which combines engineering and geology. Since our drilling wells are becoming much more challenging than ever before, it requires the office engineer not only understanding well construction knowledge but also need learn more about geology to help them address the unexpected scenarios may happen to the wells. Then a novel solution should be provided to help engineers understanding their wells better and easier in engineering and geology aspects. The digital twin technology is used to generate a suppositional subsurface world which contains downhole schematic and nearby formation characteristics. This world is described in 3D modelling engineers could read all the information they need after dealt with a unique algorithm engine. In this digital twin subsurface world, the engineering information like well trajectory, casing program, BHA (bottom hole assembly) status, are combined with geology data like formation lithology, layer distribution and coring samples. Both drilling or completion engineers and geologist could get an intuitive awareness of current downhole scenarios and discuss in a more efficient way. The system has been deployed in a major operator in China this year and received lot of valuable feedback from end user. First of all, the system brings solid benefits to operator's supervisors and engineers to help them relate the engineering challenges with according geology information, in this way the judgement and decision are made more reliable and efficiently, also the solution or proposal could be provided more targeted and available. Beyond, the geology information from nearby wells in digital twin modelling could also provide an intuitional navigation or guidance to under-constructed wells avoid any possible tough layers via adjusting drilling parameters. This digital twin system breaks the barrier between well construction engineers and geologists, revealing a fictive downhole world which is based on the knowledge and insight of our industry, providing the engineers necessary information to support their judgement and assumption at very first time when they meet downhole problems. For example, drilling engineers would pay extra attention to control the ROP (rate of penetration) while drilling ahead to fault layer at the first time it is displayed in digital twin system, which prevent potential downhole accident and avoid related NPT (non-production time). The integration of engineering and geology is a must-do task for operators and service companies to improve their performance and reduce downhole risks. Also, it provides an interdisciplinary information to end user for their better awareness and understanding of their downhole asset. Not only help to avoid some possible downhole risks but also benefit on preventing damage reservoir by optimizing the well construction parameters.

OnePetro

doi: 10.2118/214625-MS

SPE

SPE-214625-MS

SPE/IADC Middle East Drilling Technology Conference and Exhibition

Country: Asia > China (0.48)

Genre: Overview (0.47)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Asia > China > Sichuan > Sichuan Basin > Southwest Field > Longwangmiao Formation (0.99)
North America > United States > South Dakota > Williston Basin > Bakken Shale Formation (0.98)
North America > United States > North Dakota > Williston Basin > Bakken Shale Formation (0.98)
North America > United States > Montana > Williston Basin > Bakken Shale Formation (0.98)

SPE Disciplines:

Well Drilling > Drilling Operations > Drilling optimization (0.67)
Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (0.49)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (0.47)

Technology:

Information Technology > Artificial Intelligence (0.69)
Information Technology > Data Science (0.47)

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The First Application of a Cloud-Based Well Engineering Solution in the Middle East Region

Vij, Jitesh (SLB) | Garg, Ankit (SLB) | Kumar, Bimal (Crescent Petroleum) | Sedgwick, Paul (Crescent Petroleum) | Hussein, Ahmad Naim (SLB)

OnePetroMarch, 2023

Abstract Low oil prices over the past few years have led oil and gas organizations to embrace digital transformation to improve the efficiency and quality of well design. Nowadays, digital transformation and reducing well construction can have significant impact on determining the financial viability of a discovery. Teamwork and the collaboration of numerous experts in different disciplines are required to achieve a properly engineered well design that can be executed with minimal risks. Present-day well planning uses several increasingly obsolete techniques, including maintaining spreadsheets as risk registers, sharing multiple design iterations between disciplines, drilling, and geological concerns, manually replanning to accommodate changes, and people working in "silos"—often from different offices or from home. Along with this, planning software, when installed on a computer, may be difficult to maintain and update with new software releases. Often an expert in one discipline will not have visibility on the work done by other engineers, impeding collaboration. Many linear processes lead not only to increased well planning time but also to suboptimal well design resulting in higher planning and execution costs (Bello et al. 2014). Today, the oil and gas industry lag in the adoption of digital technologies and most of the ones that exist are not used commercially. Often, the reason is that these solutions address only a very small part of the entire well construction workflow. They are not fully matured, have a poor user interface, and require heavy computing power. Operators, on the other hand, are looking for a full-suite solution and they do not have the resources or expertise to connect various digital solutions existing in the market from different vendors. The need of the hour is an integrated solution that is easy to adopt, provides a collaborative work environment, is cloud-based to leverage computing power (Tanaka et al. 2018), and most importantly supports all the major well design workflows. In this paper, we discuss the first commercial application of a digital cloud-based well-planning solution in the Middle East region, which enabled Crescent Petroleum to become the first operator to adopt the system in UAE.

OnePetro

doi: 10.2118/212822-MS

SPE

SPE-212822-MS

SPE Canadian Energy Technology Conference and Exhibition

Country:

Europe (1.00)
Asia > Middle East (1.00)
North America > United States (0.95)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Drilling > Well Planning (1.00)
Management > Professionalism, Training, and Education > Communities of practice (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Knowledge management (1.00)

Technology:

Information Technology > Communications > Collaboration (0.87)
Information Technology > Artificial Intelligence > Representation & Reasoning > Planning & Scheduling (0.34)

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Successful Field Implementation of an Integrity-Focused Digital Monitoring System for Tubular Running in a Challenging Thermal ERD Application

Taubner, Spencer (Volant Products Inc) | Bordieanu, Marius (Suncor Energy Inc) | Dall'Acqua, Dan (Noetic Engineering 2008 Inc)

OnePetroMarch, 2023

Abstract Horizontal liners in extended-reach drilling (ERD) wells can experience severe loading during running. Sometimes, downhole loads approach the limits of the tubular system and must be actively managed to ensure long-term well integrity. This paper describes a Canadian thermal operator's approach to managing installation and service performance of slotted liner and wire-wrapped screen systems in a steam-assisted gravity drainage (SAGD) application with unwrapped reach ratios approaching 13:1, and the associated evolution of liner running practices. The Operator's approach combines well-characterized liner body installation loading limits and a rigsite digital solution that leverages available measurements and a real-time torque-and-drag and tubular integrity monitoring system to inform the drilling team during running. Surface loads and rates measured by the rig are used as input to top-down torque-and-drag analysis to estimate downhole load distributions. Those downhole load estimates are then compared to the local loading limits of the liner at all depths. These local loading states (and their associated uncertainties) are integrated into a safe surface loading envelope that is displayed to the drilling team and updated in real time to support running decisions. The evolution of the Operator's running practices has provided a strong basis for confidence in protecting a critical tubular system, and over 250 liner runs have been monitored to date using the digital system. Prior to implementing the system, a conservative approach to managing downhole loads during liner running was used. The integration of a strong engineering basis for the tubular structure with top-down torque-and-drag analysis and uncertainty characterization has provided a running optimization basis and measurable indicators of tubular health that can serve as an enduring quality record and be referenced for the remainder of the well life. Forecasting of running loads and liner limits to total depth has also enabled early recognition of running challenges and opportunities for optimization. Interestingly, the edge-deployed digital system has also led to operational efficiencies during the running process. Running stages involving higher risk to tubular integrity are recognized early and treated with due care, as are opportunities for increasing the efficiency of certain parts of the running process. As the Operator considers longer-reach wells, the system also provides insights into likely running challenges and provides strong history-match datasets that provide a field-calibrated basis for predicting running and tubular integrity limits. The Operator leveraged a novel digital methodology for monitoring liner system integrity during well construction. The ongoing use of this system has allowed optimization of planning, real-time, and post-run practices, and provides a well-conditioned historical dataset for future well planning. The methodology has enabled the Operator to unify work done by drilling engineers, consultants, and the rig crew for optimal liner system integrity and running efficiency.

OnePetro

doi: 10.2118/212482-MS

SPE

SPE-212482-MS

SPE/IADC International Drilling Conference and Exhibition

Country:

North America > United States (0.93)
North America > Canada > Alberta (0.68)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

North America > Canada > Alberta > Athabasca Oil Sands > Western Canada Sedimentary Basin > Alberta Basin > McMurray Formation (0.99)
North America > Canada > Alberta > Athabasca Oil Sands > Western Canada Sedimentary Basin > Alberta Basin > Firebag Oil Sands Project > Wabiskaw-McMurray Formation (0.99)

SPE Disciplines:

Well Drilling > Drilling Operations > Directional drilling (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery (1.00)

Technology:

Information Technology > Sensing and Signal Processing (0.85)
Information Technology > Architecture > Real Time Systems (0.75)

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Abstract The energy industry is undergoing a digital transformation, whose goals include increased operational efficiency and reduced energy extraction costs. Data science and machine learning (ML) are enabling the drilling engineering community to contribute to the success of these goals. An ML-based digital solution has been developed to assist the drilling engineer select an optimum bottomhole assembly (BHA) and drilling fluid technology during the well design phase. Traditionally, these selections depended on offset well analysis, which is a manual and time-consuming undertaking. As an alternative, the new digital solution, launched in the form of a web app, automatically selects similar offset wells, and evaluates the available BHA and drilling fluid options from those similar wells. The web app displays these options to the drilling engineer, who is now empowered to make fully informed data-driven decisions. To power the new digital solution, an extensive effort was made to gather, clean, and prepare global operational data into a new database. This operational database includes the selection decisions and performance results of drill bits, motor power sections, rotary steerable systems, BHA configurations, and drilling fluids. After the drilling engineer defines the parameters of the planned drilling run, a multidimensional distance-based approach is used to automatically select the most similar previous drilling runs within the context of the technology selection. The drilling engineer can also fine tune the offset selection based on experience using filters in the web app. Once the most similar offset runs are determined, the technology selection decisions are scored for numerous key performance indicators (KPIs). These KPIs, along with user-defined weights, drive the overall scores. Finally, technology selection recommendations are based on the overall scores and other contextual data such as local availability and cost. The new digital solution has been deployed to a global group of drilling engineers. Feedback sessions are held regularly, and the development team uses this feedback to rapidly iterate and improve user experience. While today's drilling engineers have access to a vast amount of data and information, it often cannot be used in a practical and efficient way. The new solution places all previous drilling system technology selection choices and results into the hands of the drilling engineers, allowing them to make their best decisions. This approach demonstrates how ML and innovative software deployment methods can truly assist the human decision-making process and succeed in accomplishing the goals of digital transformation. To our knowledge, this is a unique approach to drilling system design optimization. Not only is the approach unique, but the database developed as a portion of this effort is likely the largest drilling operations database within the industry. This paper presents all phases of the project, including the details of database creation, data preparation, development of the ML models, and the creation and iteration of the user interface. Finally, this paper presents the future of this effort as part of the company's vision to be our customers’ performance partner of choice.

OnePetro

doi: 10.2118/212559-MS

SPE

SPE-212559-MS

SPE/IADC International Drilling Conference and Exhibition

Country: North America > United States > Texas (1.00)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

North America > United States > Texas > Permian Basin > Delaware Basin (0.99)
North America > United States > New Mexico > Permian Basin > Delaware Basin (0.99)
North America > United States > Colorado > DJ (Denver-Julesburg) Basin > Niobrara Formation (0.99)
(41 more...)

SPE Disciplines:

Well Drilling > Drilling Fluids and Materials (1.00)
Well Drilling > Drilling Equipment (1.00)
Well Drilling > Drill Bits > Bit design (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology:

Information Technology > Data Science (1.00)
Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.94)

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Artificial Well Engineering Intelligence (AweI): Is It Drilling Engineer's Dream or Driller's Nightmare?

Samuel, Robello (Halliburton) | Kumar, Kiran (Halliburton)

OnePetroFebruary, 2023

Abstract Applying artificial intelligence (AI) is exceedingly difficult for drilling operations as the system is overly complex and dynamic. As a result, more comprehensive domain-general engineering mapping, also known as "artificial well engineering intelligence," is required to predict operating parameters and problems with reasonable accuracy. This paper presents a detailed overview of engineering models that are interconnected in the form of microservices to provide a more logical solution as the well is drilled. It draws out some important findings and discusses ways that results can be infused with the work on explainable artificial engineering intelligence in realtime. The results argue the logical reasoning and mathematical proof. Drilling Engineer–Driller–Rig system interaction through AweI with interconnected subdomains requires tighter integration between various engineering models. To some extent, tractable abstract knowledge at the human level is derived from analytical reasoning through engineering models. Various engineering models are connected in the form of microservices, which can be called any number of times when the optimization is carried out. The results are transferred for physical actions either to the driller or control as set points. The method presented does not claim to address all the issues as a whole. This methodology attempts, however, to present a coherent adaptive model that provides more transparency to the algorithms that can be used as operational parameters for the driller. The analysis results have shown that the convergence was very quick in obtaining an optimal solution and the predictability in the test wells has shown the best solution results under uncertainty. It has also been found that the results provide reasonable threshold values when increased data is used as the well is drilled. As long as the driller stays within the operational region, the results have shown that the operating parameters are satisfying and good enough for the desirable outcome. In other words, a near-normal engineering solution is achieved. The two major interacting bottlenecks observed in the study are (1) the absence of domain-expertise and mapping the conceptual space and (2) the valuation of the results, which can be translated into practical operational parameters. The engineering microservices to derive engineering intelligence include the following: Torsional and lateral instabilities ROP coupled bit wear Hole cleaning Casing wear BHA Drill ahead Mechanical specific energy Hydro mechanical specific energy Motor stall weight (if motor present)

OnePetro

doi: 10.2118/213686-MS

SPE

SPE-213686-MS

Middle East Oil, Gas and Geosciences Show

artificial engineering intelligence, Artificial Intelligence, artificial well engineering intelligence, asia government, calibration, driller, drilling engineer, drilling operation, engineering intelligence, intelligence, machine learning, microservice, neural network, optimization problem, Petroleum Engineer, Robello Samuel, united states government, Upstream Oil & Gas

Country:

Asia > Middle East (0.69)
North America > United States (0.68)

Genre: Research Report (0.54)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Drilling > Drilling Operations (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology:

Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (0.49)
Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.47)
Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty (0.35)

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Graph-Based Temporal Process Planning and Scheduling for Well Drilling Operations

Pavlov, Maksimilian (Skolkovo Institute of Science and Technology, Aramco Innovations LLC) | Bukhanov, Nikita (Aramco Innovations LLC) | Safonov, Sergey (Aramco Innovations LLC)

OnePetroFebruary, 2023

Abstract Well construction is the most expensive stage of oil field development. Oil and gas companies carefully calculate all possible expenditures to assure that the project of well construction and exploitation will be profitable in time. The time for every operation of well construction is strictly regulated. However, in different oil and gas companies time allotted, for example, cementing surface casing or tripping operations can differ significantly. Therefore, some oil and gas companies are unable to calculate their well construction expenses accurately and lose a significant amount of money, which can be reduced. Also, engineering teams spend a substantial amount of time developing a drilling plan for the drilling crew, which may also be fully or partially developed by automated means. We present a data-driven approach for automatic planning and scheduling of drilling operations on wells with similar design and geological characteristics, suggesting also an improved operation classification based on the IADC dictionary of drilling operations. The model for drilling operations planning is based on the directed graph traversal and process mining techniques. The algorithm takes as an input an undetailed plan, the section which is planned to be drilled, and the phase of well construction (drilling, cementing, logging). The algorithm selects the shortest path between two adjacent operations, gathers all paths together, and outputs a detailed plan with the corresponding time for each operation. For directed graph construction, we processed about 15 drilling reports from wells of a particular oil field which have similar well design and geology conditions by virtue of their geological proximity. Algorithm performance was estimated by comparing graph time against similar plan time which was calculated based on the median time of every operation in a whole dataset. Median time (P50 percentile) was used because it demonstrates objective time in terms of well construction operations. We conjecture the above based on the fact that in some cases time for tripping can be faster or slower in some wells due to geological or other conditions, and the median provides an outlier-robust estimate of the average value. Also, graph time was compared between the engineering team's proposed plan and the actual time from drilling reports. Graph construction quality was estimated using three principal metrics: the Jaccard coefficient, structural distance, and fitness similarity.

OnePetro

doi: 10.2118/213623-MS

SPE

SPE-213623-MS

Middle East Oil, Gas and Geosciences Show

algorithm, Artificial Intelligence, asia government, construction, Construction Operation, drilling engineer, drilling operation, fitness, graph, graph-based temporal process planning, jaccard coefficient, miner, mining algorithm, operation, Petroleum Engineer, planning & scheduling, relation, united states government, Upstream Oil & Gas, well drilling operation

Country:

Asia > Middle East (0.46)
North America > United States (0.28)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Drilling > Drilling Operations (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology: Information Technology > Artificial Intelligence > Representation & Reasoning > Planning & Scheduling (1.00)

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Drilling Heat Maps for Active Temperature Management in Geothermal Wells

Khaled, Mohamed Shafik (Bureau of Economic Geology, The University of Texas at Austin (Corresponding author)) | Chen, Dongmei (The University of Texas at Austin) | Ashok, Pradeepkumar (The University of Texas at Austin) | van Oort, Eric (The University of Texas at Austin)

OnePetroFebruary, 2023

Summary Geothermal energy has gained much attention as a promising contributor to the energy transition for its ability to provide a reliable, environmentally friendly source of heat and baseload power. However, drilling high-temperature (HT) reservoirs presents significant technical and economic challenges, including thermally induced damage to bits and downhole (DH) tools, increasing drilling time and cost. This paper introduces drilling heat maps for proactive temperature management in geothermal wells during well planning and real-time drilling operations phases to avoid thermally induced drilling problems. This study uses a transient hydraulic model integrated with a thermal model to predict the bottomhole circulating temperature (BHCT) while drilling geothermal wells. The model is used to generate a large volume (1,000s) of case scenarios to explore the impact of various cooling and other heat management strategies on the BHCT in the Utah FORGE field, used here as an example, covering a wide range of drilling parameters. Results are captured, visualized, and analyzed in convenient heat maps, illustrating the advantages of using such heat maps in geothermal well construction and real-time operations. Model validation with FORGE 16A(78)-32 well data and a west Texas case scenario shows good agreement between the modeling results and experimental data, with a mean absolute percentage error (MAPE) of less than 4%. There is a clear logarithmic relationship between the drilling flow rate and BHCT at a constant mud inlet temperature and a linear relationship between the mud inlet temperature and BHCT at a constant drilling flow rate. Pronounced variation of BHCT in geothermal wells is observed with mud type, mud weight, and mud viscosity. In addition, insulated drillpipe (IDP) technology is found to significantly reduce BHCT (14–44% on average for FORGE scenarios) compared to conventional drillpipe (CDP), particularly in wells with extended measured depth (MD) where other heat management technologies and strategies become less effective. Drilling heat maps can alert drilling engineers to strategies with the highest BHCT-lowering impact, allowing focused technology selection and decision-making regarding optimal temperature management during the geothermal well design phase. In addition, real-time heat maps are valuable for facilitating active temperature management and providing real-time guidance for optimal drilling parameters during daily drilling operations. In general, heat maps can help to avoid drilling problems related to the combination of HT and temperature limitations of DH equipment, which will benefit the safe and cost-efficient development of geothermal resources.

OnePetro

doi: 10.2118/210306-PA

SPE

SPE-210306-PA

SPE Journal

Country:

North America > United States > Texas (1.00)
Asia (1.00)

Genre: Research Report (0.46)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Government > Regional Government > North America Government > United States Government (0.46)

Oilfield Places:

North America > United States > Texas > Permian Basin > Delaware Basin (0.99)
North America > United States > New Mexico > Permian Basin > Delaware Basin (0.99)
Asia > China > Sichuan > Sichuan Basin (0.99)

SPE Disciplines:

Well Drilling > Drilling Operations (1.00)
Well Drilling > Drilling Fluids and Materials (1.00)
Reservoir Description and Dynamics > Non-Traditional Resources > Geothermal resources (1.00)

Technology:

Information Technology > Visualization (1.00)
Information Technology > Architecture > Real Time Systems (1.00)

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Abstract Directional wells through the 6-in. production-hole sections in the Marrat Reservoir of the Jurassic formations have traditionally required several wireline-logging and hole-conditioning runs for comprehensive petrophysical interpretation and completion design. As the planned well inclinations increase to maximize reservoir exposure and sweep efficiency, wireline deployment poses significant challenges due to the increased risk of losing the bottomhole assembly (BHA) in the hole. Over time, logging-while-drilling (LWD) tools have become preferable for the asset team, where the tools are run either in the drilling BHA or during a dedicated wiper trip after the section has been drilled to total depth (TD). Using LWD tools in this application also reduces well delivery times and costs. A comprehensive logging solution was required to drill the 6-in. reservoir section of a study well. The complex LWD string, consisting of gamma ray, resistivity, neutron porosity, azimuthal density, azimuthal sonic, and nuclear magnetic resonance (NMR) tools, was deployed on a motorized rotary steerable system (MRSS) BHA. In addition, a prototype high-resolution acoustic imaging and caliper tool, designed to be run in both water-based mud (WBM) and oil-based mud (OBM), was also included. The acquired logging data were used for enhanced formation evaluation. Fracture and borehole breakout interpretation from the image data played a key role in the successful completion design. This ultimately led to Kuwait’s first successful “hexa-combo” LWD drilling run and the country’s first LWD ultrasonic imaging tool run in OBM in this hole size, with 13.3 ppg OBM with a maximum downhole temperature of 275°F.

OnePetro

doi: 10.30632/PJV64N1-2023a4

SPWLA

SPWLA-2023-v64n1a4

Petrophysics

Country: Asia > Middle East > Kuwait (1.00)

Geologic Time: Phanerozoic > Mesozoic > Jurassic (0.48)

Geophysics: Geophysics > Seismic Surveying > Borehole Seismic Surveying (1.00)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > Dhabi Field > Hith Formation (0.99)
Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > Dhabi Field > Gotnia Formation (0.99)
Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > Dhabi Field > Burgan Formation (0.99)
(2 more...)

SPE Disciplines:

Well Drilling > Drilling Operations (1.00)
Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)

Technology: Information Technology > Sensing and Signal Processing > Image Processing (1.00)

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Bottomhole-Assembly Dynamics Software Helps Mitigate Twistoffs While Drilling

Carpenter, Chris (JPT Technology Editor)

OnePetroDecember, 2022

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202174, “Mitigating Twistoffs While Drilling With the Help of Bottomhole-Assembly Dynamics Software,” by Mario A. Rivas, SPE, Andres A. Ramirez, and Bader S. Al‑Zahrani, SPE, Saudi Aramco, et al. The paper has not been peer reviewed. _ A major challenge during drilling operations is the occurrence of twistoffs on bottomhole assembly (BHA) components. To overcome this challenge, a study was performed of twistoffs experienced on BHA components. Based on the findings, drilling operations and recommendations were provided to reduce or eliminate twistoffs related to suboptimal drilling parameters. This analysis will help drilling engineers and personnel foresee vibration dysfunctions and act accordingly with the use of BHA dynamics software to optimize drilling parameters before and during drilling. Twistoffs Caused by Drillstring Vibrations Field experience has shown that unwanted drillstring vibrations lead to failures, especially stick/slip (torsional vibrations) that occurs approximately 50% of the time during drilling. Three main types of vibrations can be distinguished: torsional (stick/slip oscillations), axial (bit bouncing), and lateral (whirling motion caused by an imbalanced drillstring). These three types of vibration can occur at any time during drilling. Induced axial vibrations at the bit can lead to lateral vibrations in the drillstring and BHA, and axial and torsional vibrations can be observed at surface. Sometimes the severe axial vibrations close to the bit may not be observed at surface, which may lead to a potential twistoff if drilling parameters are not changed and optimized. Additionally, fatigue failure is intensified with high vibrational loads, specifically at curved well trajectories or in buckled drillstring sections as shown in Fig. 1, where high bending stresses occur. The most critical fatigue damage will happen when the drillstring is in resonance with one of its natural frequencies, resulting in twistoff events at a much lower drillstring component yield strength. The objective of the study described in the complete paper is to pursue an integrated approach considering the use of vibration-analysis software in the design of a BHA to identify safe operating windows for rotary speed and weight on bit (WOB) to prevent buckling and analyze fatigue. BHA Dynamics Resonance occurs when the rotary speed is very close to one of the natural frequencies for torsional vibration (the primary cause of failure), and WOB natural frequency for flexural vibrations of the BHA. When the frequency of any excitation is one of the natural drillstring frequencies, then the drillstring will resonate and vibration levels will be highest. With very high amplitudes, vibrations will accelerate drillstring and BHA fatigue. To estimate the critical rotary speed (resonance frequency), the BHA can be simulated using available BHA dynamics and vibration software. This software can analyze downhole vibrations; its simulations have matched several cases very closely to what the operator has experienced. Three different examples were analyzed and presented in the complete paper. The software uses nonlinear vibration theory to determine drillstring-resonance frequencies.

OnePetro

doi: 10.2118/1222-0072-JPT

SPE

SPE-1222-0072-JPT

Journal of Petroleum Technology

asia government, bending, BHA design, drill pipe selection, drilling engineer, Drilling Equipment, drilling operation, drillstring design, drillstring dynamics, dynamic software help mitigate twistoff, Engineer, erratic torque, frequency, resonance frequency, Saudi Arabia government, software, twistoff, Upstream Oil & Gas, vibration, vibration software

Country: Asia > Middle East > Saudi Arabia (0.55)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Government > Regional Government > Asia Government > Middle East Government > Saudi Arabia Government (0.55)

Oilfield Places: North America > United States > Texas > Sabinas - Rio Grande Basin > May Field > Frio Formation (0.99)

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Well Drilling > Drillstring Design > Drillstring dynamics (1.00)
Well Drilling > Drillstring Design > Drill pipe selection (1.00)
Well Drilling > Drillstring Design > BHA design (1.00)
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Technology: Information Technology (0.49)

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