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Course Details

A laptop is required.

• Providing engineers and geoscientists with an alternative (new and innovative) set of tools and techniques to solve E&P related problems.
• Identifying remaining reserves and sweet spots in reservoirs as a function of time and different field development strategies.
• Optimizing stimulation and workover design and effectiveness by coupling reservoir characteristics with stimulation practices and forecasting stimulation outcome.
• Tapping into the hidden and usually unrealized potentials of numerical reservoir simulation models.
• Quantifying uncertainties associated with geological models and other parameters used in modeling production optimization and recovery enhancement.

Intended Audience

This course is designed for reservoir, completion and production engineers of operating companies as well as service company personnel involved with planning, completion and operating wells.

Course Description

This short course will start with the fundamentals of Artificial Intelligence and Data Mining (AI&DM) covering artificial neural networks, evolutionary computing, and fuzzy logic. The course is devoted to field application of this technology with focus on production optimization and recovery enhancement.

Artificial Intelligence is a collection of several analytical tools that attempts to mimic life. This technology is used extensively in other industries such as automation and manufacturing, financial market and home land security. It has been predicted that use of AI technology will introduce a step change in how E&P industry does business in the future.

This short course examines the successful application of AI&DM in the E&P industry in the past several years.  These applications include Modeling and Optimization of Stimulation Designs and Practices and Identification of Candidate Wells, Reservoir Characterization, Optimization of Drilling Operations, New Workflows for Reservoir Simulation and Modeling that provide fast screening of the reservoir for identification of remaining reserves and optimum infill locations.

Topics covered include the following:

• Artificial Intelligence & Data Mining; an overview
• Artificial Neural Networks, Evolutionary Computing and Fuzzy Logic
• Field Applications & Hands on exercises
• Empirical Modeling and Optimization of Stimulation Practices
• Best Practices Analysis and Well Candidate Selection
• Top-Down, intelligent Reservoir Modeling
• Fast screening of alternative field development strategies.
• Identification of Remaining Reserves and Sweet Spots as a function of time and Optimum Infill Locations.
• Identification of Underperformer Wells.
• Surrogate Reservoir Modeling
• Replication of the results of numerical simulation models in seconds.
• Unleashing the true potential of reservoir simulation models.
• Quantification of uncertainties using Monte Carlo Simulation method.

CEUs

1.6 CEUs (Continuing Education Units/8 hours) awarded for this 2-day course.

Cancellation Policy

A fee equal to 25% of the course fee will be charged for cancellations less than 15 working days before the course begins. No refunds will be made for cancellations after the course begins.