... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... 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...

... haskett pilot program correct choice machine learning log reserve variance Standard Deviation precision Drilling Result lognormally equation unconventional reservoir society of petroleum engineers Introduction Suppose we plan to develop a field by drilling up to N wells. Each well i...

... ranking prospects. Decision Model – The Resource Assessment (RA) Model Shoemaker 1 has presented a pyramid of approaches for decision making, which is reproduced in Figure 1 . The decision model described in this paper is an application of Shoemaker's theory of decision choices. machine...

... cash flow input variable variation NPV offshore field PECE module oil price machine learning Project economics investment production forecast noise forecast probabilistic approach contribution Standard Deviation Introduction Hence, a method is required to convert the future...

... government Bayesian Inference Upstream Oil & Gas small return-on-investment ratio information probability distribution unconventional play Artificial Intelligence complex reservoir frequency good well productive well break-even frequency machine learning Drillstem Testing risk management...

..., 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 simulation inverse dependence structure marginal distribution...

... machine learning reserves evaluation feasibility extraction quantity mining operation How Is The UN Involved in Petroleum Reserves/Resources Terminology? A globalized economy requires a globally harmonized mineral reserves/resources terminology to support international energy studies...

... 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...

... Reservoir Characterization Upstream Oil & Gas porosity machine learning reservoir simulation different geological model geologic modeling Artificial Intelligence information project volatility reference model Snesim reference truth model forecast permeability oil production...

.... machine learning upstream oil & gas misinterpret development well recovery strategic planning and management drillstem testing accuracy assessment uncertainty reduction artificial intelligence risk management appraisal program interpretation information source drillstem/well testing...