1. Ahmed S. Amer, Global Technical Services Sr. Manager. Newpark
Presenting – “Digitizing Drilling Fluids; Opportunities & Challenges”
This presentation will present an overview of efforts around digitizing drilling fluids in comparison to the broader digitalization and automation effort of the drilling process.
· Focus on how fluids analytics can help in offset well analysis
· Identify and improve data quality and hence confidence level in data-driven decisions
· Integrate Public data for bench-marking
· Tie fluids data to engineering data models
· Review visualization needs
· Review of where the opportunities exist and what the challenges that need to be overcome.
Ahmed Amer is Newpark's Sr. Manager for Global Technical Services supporting global client operations and leading the global technical community by integrating fluids experience, software tools and laboratory testing together for best-in-class client experience.
Ahmed’s career spans over 16 years during which he held field, operational, technical and R&D roles in fluids and pressure control domains with a focus on deepwater operations and lost circulation solutions.
He is also a member of API Subcommittee 13, Chairman of the 2020 and 2022 AADE Fluids Conference and is the Chairman for AADE Fluids Management Group. Ahmed has served as an advisor to two graduate university programs, holds IP, has authored 30+. Ahmed is also an SPE Distinguished Lecturer for the 2020-2021 tour.
2. Dr. Kriti Singh, Senior Research Data Scientist, Corva
Presenting – “Closed Loop Drilling Automation with Integrated ROP Optimizer using Big Data Analytics and ML”
This presentation offers an in-depth exploration of Predictive Drilling, shedding light on the profound influence of advanced technologies such as big data analytics and machine learning on real-time drilling operations, with a specific focus on optimizing the Rate of Penetration (ROP). Delving into Corva's significant contributions over a five-year span, the presentation highlights four technical papers presented at SPE conferences, showcasing their pivotal role in realizing closed-loop drilling automation. The integration of drilling fluids, big data analytics, and machine learning techniques is dissected, revealing their collective capacity to meticulously analyze extensive datasets, unveil underlying patterns, and empower strategic decision-making processes, consequently leading to remarkable gains in operational efficiency. This presentation serves as an enlightening window into the future of enhanced drilling processes.
Kriti Singh is a Senior Research Data Scientist at Corva, bringing extensive expertise in the field of petroleum engineering. With a Ph.D. in Petroleum Engineering from The University of Tulsa, Kriti has dedicated the past five years to the Research and Development team at Corva. Kriti's contributions have been instrumental in the development of cutting-edge technologies, resulting in numerous authored and co-authored technical papers in collaboration with major oil and gas operators. Recognized as an active member of the Oil and Gas community, Kriti actively participates in webinars, and energy panels, and delivers technical presentations at prestigious conferences worldwide.
3. Siva Rama Krishna Jandhyala, Technology Advisor – Engineering, Halliburton
Presenting – “Digital Approach to Designing Cement Thickening Time”
The goal of any cement job is to achieve zonal isolation by placing a cement barrier across critical formations. To achieve this, cement slurries must be tailored to remain pumpable throughout the placement process. Pumpability is quantified through thickening time (TT) test. A slurry design team iteratively adjusts the composition and additives to tailor the TT of the slurry for well specific temperatures and pressures. The process is primarily manual and relies on the experience of the design team in using the materials. This increases the number of iterations and thus the slurry design cost and time. Digital technologies can be used to analyze historic test data and assimilate the learnings into mathematical models. These models complement design team experience by predicting TT as a function of slurry composition and test conditions. Design teams can digitally evaluate multiple options and select the most suitable composition for further testing. This approach significantly reduces the slurry design risk, as well as reducing time and costs.
Mr. Jandhyala is an Advisor with Cementing Technology group at Halliburton Energy Services Inc. He has over 13 years of R&D experience. His area of work encompasses Cementing fluids design, Cement Job Design & Analysis, Near Wellbore Integrity Assessment, Cementing for CCS wells. His recent interests are in building data driven methods that reduce the risk, cost and time associated with cement job design, execution and evaluation.