... deformation occurring in the structure. In this analysis the basic feature geometric parameters, slot width, slot length, slot depth, OD and ID were considered. The analysis was carried out with 2 levels (Upper and lower limit) of each input parameter as shown in Table 3-2 . The nominal base values of each...

... fracturing materials machine learning wellbore integrity reservoir geomechanics hydraulic fracturing proppant fracturing fluid wellbore design input parameter breakdown pressure petroleum engineer tensile strength neural network abdulraheem ann model cylindrical sample dataset borehole...

... bubble point pressure empirical correlation elastic net regression algorithm equation society of petroleum engineers solution gas-oil ratio statistical analysis dataset input parameter Introduction The phase behavior and nature of reservoir fluids are critical in reservoir engineering...

... learning methods offer insights that could improve response time and strategies for treating stuck pipe. transfer function Exhibition machine learning input parameter prediction Upstream Oil & Gas kernel function Artificial Intelligence Support Vector Machine SVM jarring operation...

... research and development using additional data as time goes on along with more advanced numerical simulation and data analysis models. flow in porous media Simulation prediction machine learning Fluid Dynamics input parameter Artificial Intelligence porous medium predictor Upstream Oil...

... transition from one branch to another. While the range of fluid properties is considered to be very wide, we were able to keep the input parameters to a minimum in terms of defining the character of the fluid (molecular weight and specific gravity). We demonstrated that the proposed correlation performs much...

... decisions. Artificial Intelligence average fracture conductivity Simulation stimulation design Reservoir Characterization machine learning fracture characterization fluid type input parameter Upstream Oil & Gas single fracture configuration fracture conductivity hydraulic fracturing...

... intake pressure society of petroleum engineers input parameter Telemetry data spectrum intake temperature machine learning Euclidean Distance oilfield facility analysis data analysis thermogram power consumption deviation value Introduction The late stage of oilfield development...

... log analysis conventional approach clean sand end point input parameter porosity greater dolphin area evaluation reservoir saturation conventional evaluation In addition, the LowReP generates a net-to-gross (NTG) log curve showing that the laminated clean thin-bed sands interval has NTG...

... selection and formulation complex reservoir mud loss problem Simulation pressure distribution real time system drilling fluids and materials fracture stiffness input parameter drilling fluid chemistry hydraulic fracturing Upstream Oil & Gas mud loss incident fracture deformability drilling...

... stability model is set up, as of constitutive equation and failure criteria selection. Based on available data, a stochastic approach is used to assess the uncertainty associated to input parameters, or otherwise other alternatives like expert opinion are utilized. Secondly, a sensitivity analysis...

..., and the second part of the data is used to verify the accuracy of the prediction results from each input parameter. The results were analyzed and compared with classic Arps decline models. production control Reservoir Surveillance machine learning production monitoring shale gas production prediction...

... and engineers have used to address the uncertainty-problem in the past. geologic modeling Reservoir Characterization reservoir simulation evolutionary algorithm optimization problem dissimilarity matrix input parameter geological modeling enhanced recovery Upstream Oil & Gas information...

..., and downstream processing. fuzzy logic transition mechanistic model flow pattern regime smooth pipe Upstream Oil & Gas fuzzy system pressure drop Artificial Intelligence inclination angle input parameter prediction flow regime input variable fuzzy inference system identification crisp...

... for improving model predictive ability. lh design input parameter machine learning alternative approach predictor Artificial Intelligence traditional approach training data Upstream Oil & Gas Simulation co 2 bb design response surface prediction model fit subsurface storage...

... outcomes. In this paper we use Monte Carlo simulation and probability density functions (PDFs) that describe likely values of fracture half-height as an input parameter into reservoir models. PDFs and Cumulative Distribution Functions (CDFs) are used to provide realistic estimates of stimulation parameters...

... are calculated and compared to existing experimental data. The mechanistic model shows significant improvement in pressure drop predictions. Dimensionless groups from Buckingham Pi theory are used to investigate the sensitivity to the input parameters. The use of dimensionless groups reduces the number...

... likely flow rate at current conditions. machine learning Artificial Intelligence production control flow metering production monitoring Drillstem Testing Upstream Oil & Gas Simulation input parameter outlier estimation Reservoir Surveillance neural network drillstem/well testing...

.... An offshore development was modeled, using uncertain inputs for determining OOIP, recovery and a mean-reverting oil price model. In the base (no overconfidence) model, the input parameters for the OOIP, recovery and economic calculations were all drawn via Monte Carlo simulation from appropriate, pre...

... equilibrium price project valuation log norm 0 future price price model Standard Deviation Artificial Intelligence Upstream Oil & Gas input parameter characteristic historical data asset and portfolio management fluctuation variability case statistics oil price normal distribution...