Landmark Graphics Corporation

Xinli Jia

Srinath Madasu

Andrey V Filippov

Keshava Prasad Rangarajan

Vitaly Khoriakov

Da Pang

System for optimizing operation of an oil and gas well employs multi-objective Bayesian optimization of wellbore parameters to minimize scaling and corrosion. The system may contain instrumentation for measuring temperature, pressure, at least one production parameter and at least one ion concentration of the fluid in the wellbore. The system may also have a processor for performing a calculation procedure to determine an anticipated corrosion rate ('Vbase') and a scaling index (“Is”) reflecting a tendency of scale to form in the wellbore based on the measurements provided by the instrumentation, where Vbase and Is are calculated along the length of the wellbore. Based on a selected set of optimization points taken from the calculations of Vbase and Is, the system may control the alkalinity and flow rate of the fluid based on the multi-objective optimization to simultaneously optimize scaling and corrosion.

Multi-objective optimization on modeling and optimizing scaling and corrosion in a wellbore

Methods and systems are presented in this disclosure for performing fast economic analysis of production by fracture-stimulated wells. A class of models can be defined by combining a simulated fracture geometry comprising a stimulated reservoir volume with accounting for fluid dynamics and phase transitions in the stimulated reservoir volume for modeling production in a plurality of reservoirs. An objective function related to the production in the plurality of reservoirs can be generated based on at least one model from the class of models. Parameters related to fracture stages of a fracture network can be then determined, based on the objective function, and communicated, via a computer network to a computing device, to be used for at least one of building or operating the fracture network in the reservoir.

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Sugar Land, TX, United States of America

Xinli Jia