000			01535nam a2200205Ia 4500
005			20250408165437.0
008			230421s2020||||xx |||||||||||||| ||eng||
020			_a9780128209578
041			_aEnglish
082			_a006.31 S86
100			_aSun, Shuyu _eAuthor _92163
100			_aZhang, Tao _eCo-Author _92166
245		0	_aReservoir simulations : machine learning and modeling
260			_aUnited Kingdom: _bGulf Professional Publishing, _c2020.
300			_aviii, 332p.; 21cms.
500			_aReservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research and technology. This reference explains common terminology, concepts, and equations through multiple figures and rigorous derivations, better preparing the engineer for the next step forward in a modeling project and avoid repeating existing progress. Well-designed exercises, case studies and numerical examples give the engineer a faster start on advancing their own cases. Both computational methods and engineering cases are explained, bridging the opportunities between computational science and petroleum engineering. This book delivers a critical reference for today’s petroleum and reservoir engineer to optimize more complex developments.
650			_aArtificial intelligence _xMachine learning _92164
650			_aArtificial intelligence _xComputer simulation _92165
942			_cBK
999			_c784 _d784