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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179955-MS
... the P50. Through such quantitative evaluations of all the realizations, geologists and reservoir engineers can select optimistic to pessimistic realizations to aid economic assessment of the reservoir. Artificial Intelligence machine learning porosity property porosity similarity geobody...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179951-MS
... of exploration opportunities. asset and portfolio management portfolio assessment Artificial Intelligence Upstream Oil & Gas value assessment evaluation dependency portfolio optimization constraint optimized exploration planning machine learning Portfolio analysis cash flow probability...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179962-MS
... shale gas unconventional resource economics break-even price supply and demand pricing supply and demand forecasting complex reservoir oil company regression analysis oil shale service provider Halliburton machine learning shale oil Upstream Oil & Gas Baker Hughes service company...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179952-MS
... and portfolio management reserves replacement machine learning unconventional resource economics complex reservoir natural fracture interference performance variation evaluation symposium oil play reliable technology reliable technology paradigm estimation Indicator Upstream Oil & Gas...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179980-MS
... decision trees, Bayesian networks and, more recently, Markov chains. Newly developed machine-learning techniques combine these two separate streams of uncertainty analysis into a framework that promises to address both the quantification and aggregation of uncertainty in an objective way. What seems like...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179976-MS
... Conference case study machine learning demand dynamic society of petroleum engineers saudi arabia Upstream Oil & Gas simulation result production rate sanction main variable oil market differential equation prediction Introduction Uncertainty is an attached feature of the market...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179958-MS
... application of our method using field examples from four major shale plays. hydraulic fracturing machine learning Upstream Oil & Gas pressure transient analysis pressure transient testing detection production data histogram neighbor Artificial Intelligence pressure data local outlier...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179984-MS
... regression completion shale gas lateral length variability machine learning Upstream Oil & Gas ikonnikova complex reservoir information production function productivity producer economic analysis recovery shale gas play fluid usage coefficient marcellus play resource density algorithm...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179992-MS
... of the spread and a field application. The study covers all decline models (exponential, hyperbolic and harmonic models) and both cases where the decline exponent is known and unknown. production control production monitoring machine learning Artificial Intelligence production forecasting variance...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179960-MS
... Economics Bayesian Inference cumulative production Montney formation machine learning Upstream Oil & Gas mean eur production data reliability appraisal strategy lognormal distribution reservoir production period ultimate recovery lognormally appraisal well appraisal programme...
Proceedings Papers

Paper presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, May 17–18, 2016
Paper Number: SPE-179996-MS
... quality decisions. Artificial Intelligence risk management Energy Economics asset and portfolio management Bayesian Inference project valuation complex reservoir machine learning Project economics estimates of resource in place Upstream Oil & Gas well population Bayesian method...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169841-MS
... the future prospects for the field. Artificial Intelligence Energy Economics mean reserve Upstream Oil & Gas information assumption probability pilot well decision analytic complex reservoir haskett pilot program correct choice machine learning log reserve variance Standard...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169855-MS
... ranking prospects. machine learning SAGD thermal method Artificial Intelligence reservoir performance prediction regression assessment enhanced recovery Upstream Oil & Gas plateau period input data prospect SOR Reservoir Characterization steam-assisted gravity drainage...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169845-MS
... module oil price machine learning Project economics investment production forecast noise forecast probabilistic approach contribution Standard Deviation Introduction The estimate of a project's NPV is one of the main processes for a company that operates in the petroleum sector and has...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169847-MS
... information probability distribution unconventional play Artificial Intelligence complex reservoir frequency good well productive well break-even frequency machine learning Drillstem Testing risk management drillstem/well testing test well perfect information Decision Entropy Theory society...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169867-MS
... Energy Information Administration machine learning Upstream Oil & Gas pricing pricing structure natural gas production artificial neural network spe hydrocarbon economics US government gas production neural network framework natural production natural gas spot price natural gas natural...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169857-MS
... measures. The work is divided into five sections: introduction, stochastic processes and copula theories, integration methodology, applications, results and conclusions. asset and portfolio management reserves evaluation Artificial Intelligence Upstream Oil & Gas machine learning reservoir...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169860-MS
... system realistic assumption application Artificial Intelligence Framework Classification foreseeable future fossil energy development project Viability petroleum mineral reserve Market Condition deposit machine learning reserves evaluation feasibility extraction quantity mining...
Proceedings Papers

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014
Paper Number: SPE-169825-MS
... analysis. This study could help answer the question of how much detail in reservoir models are necessary if the end objective is to obtain realistic assessment of net economic risk (which would be used to make correct decisions)? Reservoir Characterization Upstream Oil & Gas porosity machine...

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