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Learn more about training courses being offered. Learn more about training courses being offered. This course covers the fundamental principles concerning how hydraulic fracturing treatments can be used to stimulate oil and gas wells. It includes discussions on how to select wells for stimulation, what controls fracture propagation, fracture width, etc., how to develop data sets, and how to calculate fracture dimensions. The course also covers information concerning fracturing fluids, propping agents, and how to design and pump successful fracturing treatments. Learn more about training courses being offered. Current and future SPE Section and Student Chapter leaders are invited to engage and share. Every attendee leaves energised with a full list of ideas and a support network of fellow leaders. Those sections and student chapters actively participating in this workshop have consistently been recognized with awards as the best in SPE. SPE Cares is a global volunteering drive aimed at promoting, supporting and participating in community services at the SPE section and student chapter’s level. On its official launch this year at ATCE Dubai, SPE Cares will conduct a “Give a Ghaf” Tree Planting Programme to help preserve Ghaf’s cultural and ecological heritage. The Ghaf tree is an indigenous species, specific to UAE, Oman and Saudi Arabia. It is a drought tolerant, evergreen tree that can survive a harsh desert environment. The initiative not only aims to hold events/activities at ATCE, but also recognise community service that SPE members are already conducting in their respective student chapters and professional sections. The KEY Club, open daily, is an exclusive lounge for key SPE members. The lounge is open to those with 25 years or more of continuous membership, Century Club members, current and former SPE Board officers and directors, Honorary and Distinguished Members, as well as this year’s SPE International Award Winners and Distinguished Lecturers. DSATS (SPE’s Drilling Systems Automation Technical Section) will hold a half-day symposium featuring keynote presentations on urban automation. This symposium will explore technologies being used in developing smart cities through the automation of their infrastructure, transportation systems, energy distribution, water systems, street lighting, refuse collection, etc. These efforts rely on many of the same tools needed for drilling systems automation yielding increased efficiencies, lower maintenance and reduced emissions. Their knowledge and experience can guide the path being travelled by the oilfield drilling industry.
What Damage Is Wrought by the Rush to Shut In Wells? The Permian Basin is now influencing the upstream water market on the way down, while many questions swirl around the implications of unprecedented shut-ins. Autonomous Inflow Control Valve technology demonstrates significant benefits within first year. As operators feel the pinch of low oil prices, so, too, do their service providers. The room for error and cost overruns just got a lot smaller with the escalating need to make operations more efficient and leaner with fewer resources and investors continuing to prioritize ESG alongside profitability.
The cementing services market size in the US is expected to drop 50% year-on-year from 2019. The significant drop in Permian Basin activity will account for 40% of the total market size reduction. The complete paper presents a case study in which offline cementing improved operational efficiency by reducing drilling times and provided significant cost savings. This year, excellent papers have been presented, augmenting our knowledge and responding to the challenges of complex wells and efficiency requirements. At the same time as we “Strengthen the Core,” we continue to focus on design, delivery, and evaluation of cementing operations.
Autonomous Inflow Control Valve technology demonstrates significant benefits within first year. As operators feel the pinch of low oil prices, so, too, do their service providers. The room for error and cost overruns just got a lot smaller with the escalating need to make operations more efficient and leaner with fewer resources and investors continuing to prioritize ESG alongside profitability. The objective of this study is to show how the capacitance-resistance model (CRM) was used on this field and how it validated the use of other independent methods. This paper demonstrates that integration of different sources of data in reservoir management is critical.
Summary We report here a study of lithology-controlled stress variations observed in the Woodford shale (WDFD) in north-central Oklahoma. In a previous study, we showed that the magnitude of the minimum horizontal stress S hmin systematically varied with the abundance of clay plus kerogen in three distinct WDFD lithofacies. We believe that the application of the workflow described here in the context of viscoplastic stress relaxation can facilitate the understanding of layer-to-layer stress variations with lithology and thus contribute to improved HF effectiveness. Introduction Development of extremely low permeability unconventional oil and gas reservoirs requires multistage HF in horizontal wells. It is wellestablished that the magnitude of the three principal stresses and their relative differences significantly influence the initiation, propagation, and containment of hydraulic fractures (cf., Economides and Nolte 2000; Fisher and Warpinski 2012; Desroches et al. 2014; Xu et al. 2017; Zoback and Kohli 2019). More specifically, layer-to-layer stress variations influence optimal landing zone selection, vertical hydraulic fracture growth, and proppant placement (cf., Fu et al. 2019; Singh et al. 2019). Thus, to effectively stimulate the formations being produced from, one has to understand the physical properties of the formations being stimulated as well as the state of stress within, above, and below the producing units. Ma and Zoback (2017) reported variations of stress magnitudes obtained from HF stages in two horizontal wells that encountered three distinct lithofacies of the WDFD in central Oklahoma. They hypothesized that the abundance of compliant components (principally clay and organic matter, or kerogen) brought about the observed stress variations between the three WDFD lithofacies.
This paper focuses on the preparation for, and implementation of, well-control training, while highlighting the integration of people skills into curricula and what advantages operators and drilling contractors have obtained. This paper describes the mobilization of a snubbing unit and blowout preventer (BOP) stack in the Middle East that enabled a well with an underground blowout and surface broaching to be brought under control within a short time. Field N is a complex heavy-oil field in the north of the Sultanate of Oman. The dynamic behavior of Field N is characterized by strong aquifer and is dominated by bottomwater drive. This paper presents the design considerations, methodology, and results of two deepwater MPC operations conducted to cement production casing strings within a target operating window of approximately three-tenths of a pound.
This one-day training event introduces completion, production, surveillance and reservoir engineers to the design of fiber-optic DTS (distributed temperature sensing) and DAS (distributed acoustic sensing) well installations. A basic understanding of the principles and benefits of DTS, DAS and surveillance monitoring technology, in general, is assumed. This course provides both an overview of water management and an in-depth look at critical issues related to sourcing (acquiring), reusing, recycling, and disposing of water in hydraulic fracturing operations. The course starts with a background of hydraulic fracturing operations and the different plays around North America. Options being used for transport, storage, reuse, and disposal are described for each of the different regions.
Xu, Rui (University of Texas at Austin) | Deng, Tianqi (University of Texas at Austin) | Jiang, Jiajun (Baylor University) | Jobe, Dawn (Aramco Services Company: Aramco Research Center, Houston) | Xu, Chicheng (Aramco Services Company: Aramco Research Center, Houston)
Diagenetic effects in carbonate rocks can enhance or occlude depositional pore space. Reliable identification of porosity-enhancing diagenetic features (e.g., vugs and fractures) is essential for petrophysical characterization of reservoir properties (e.g., porosity and permeability), construction of geological and reservoir models, reserve estimation, and production forecasting. Challenges remain in characterizing these diagenetic features from well logs as they are often mixed with variations in mineral and fluid concentrations. Herein, we explore a data-driven approach that is based on a comprehensive well log data set from the Arbuckle Formation in Kansas to classify vuggy facies in carbonate rocks. The available well log data include conventional logs (gamma ray (GRTC), resistivity (RT), neutron/density porosity (NPHI/RHOB), photoelectric factor (PE), and acoustic slowness) and nuclear magnetic resonance (NMR) transverse relaxation time (T2) logs. We parameterized the measured T2 distribution using a multimodal lognormal Gaussian density function and combined the resulting Gaussian parameters with conventional logs as inputs into three supervised machine learning (ML) algorithms; namely, support vector machine (SVM), random forest (RF), and artificial neural network (ANN). The facies labeling data used in this study were based on visual examination of vug sizes from core samples, which include five classes; namely, nonvuggy, pinpoint-size, centimeter-size, fist-size, and super-vuggy. In total, 80% of the data set was used as the training set, and a fivefold cross validation was used for hyperparameter tuning. We conducted a detailed comparison of the above three ML algorithms on the basis of different combinations of features. The highest classification accuracy achieved on the holdout testing set is 84% using SVM on a combination of conventional logs and selected NMR Gaussian parameters as inputs. In general, inclusion of conventional log data improves the prediction accuracy compared with using NMR data alone. Feature selection improves the performance for SVM and ANN but is not recommended for RF.
Yogashri is a reservoir engineer for Endeavor Energy Resources. At Endeavor, she is involved with field development planning for unconventionals in the Midland Basin. She's also worked as a senior production engineer for Texas Oil and Gas Institute and Devon Energy, overseeing various production optimization studies and field operations in the Permian Basin. Yogashri is an active SPE member at the local and international levels through technical conference committees, study groups, authoring/coauthoring seven technical publications, and community service initiatives. She is the recipient of Houston Engineers Week Young Engineer of the Year representing SPE-Gulf Coast Section for 2018 and the International Young Member Outstanding Service Award from SPE in 2018.
Coiled tubing (CT) milling of downhole plugs in large monobore completions is considered one of the most challenging CT workover operations, especially when conducted in offshore environments where intervention workflows are driven by efficiency gains for operators and service companies alike. Experience gained from milling operations using CT instrumented with real-time data enabled measurable improvements in efficiency. Post-job data analysis offered additional insights to improve methodologies and further unleash untapped efficiencies.
Real-time bottomhole assembly data were collected during plug milling operations using a positive displacement motor. Critical downhole readings, such as CT internal and annular pressure, axial force (thrust), and torque were monitored during the operation to identify tagging of isolation plug targets, onset of milling, and stalls. The real-time data not only added confidence to event confirmation, but also increased the accuracy in estimating efficiency metrics such as rate of penetration (ROP) and stall recovery duration.
Post-job analysis calculated the error and shortcomings associated with estimating event detection based on surface measurements. Additionally, error in event detection was tied back to inaccuracies in estimating efficiency metrics when relying on surface measurements alone.
Analysis of downhole measurements in CT milling improves the precision of event detection and enables rapid reactions. Target tagging reflects instantly in thrust, and motor activation reflects synchronously in downhole differential pressures and torque, which together provide certainty of motor engagement on the target. Stalls reflect in differential pressure and torque spikes that coincide with motor specifications. ROP more than doubled by leveraging these event detection techniques throughout milling operations.
New torque-thrust signatures were also identified to detect material interfaces. Changes in signature behavior indicated when the bit milled through one target and reached the next. This is particularly useful when the operator must mill through a target but stop at a subsequent, contiguous one. Post-job data also suggested that some events may have been mistaken as stalls during the operation, with downhole data confirming they were false positives. Finally, at operating conditions in the case study, a 7-second lead-time window was identified to anticipate and react to stalls. This highlights the importance of access to real-time downhole information, such as differential pressure, to avoid both stalls and false positives, and ultimately, to make breakthroughs in operational efficiency.
Integrated analysis of downhole measurements during CT milling lent visibility to actual ROP, stall rates, and stall recoveries. These constitute important baselines against which any improvement in efficiency must be compared. The methodologies proposed here for event detection, with special attention to stall anticipation and milling interface detection, pave the way for smarter, more efficient operations.