... on the big data, the multi-level evaluation system was established by using the analytic hierarchy process (AHP). Then, the weight factor was calculated to uncover key factors that dominate productivity of MFHWs. Finally, the fuzzy logic method was used to calculate the Euclidean distance and quantitatively...

.... The ANFIS model also has the lowest average percent relative error (APRE), root mean square error (RMSE), and standard deviation (SD) of -0.09, 1.01, 0.0075, respectively. artificial intelligence reservoir simulation upstream oil & gas fuzzy logic trend analysis api gas solubility relative...

... management. This perspective will improve efficiency of operations in addition to having the privilege of universality, where it can be applicable for different well groups. The rising wave of digitalization is anticipated to improve field operations, business performance, and production safety. fuzzy...

... machine learning energy economics reservoir characterization fracturing materials reservoir geomechanics risk management well logging shale oil log analysis flow in porous media pattern recognition data mining artificial intelligence shale gas fuzzy logic equation of state...

... intelligence reservoir simulation fluid dynamics tdm limitation data quality fuzzy logic soft computing subsurface uncertainty oil rate production performance history matching artificial neural network application reservoir model A Historical Overview Artificial Intelligence The term...

... fuzzy logic was introduced. Being a soft-computing pattern recognition method that allows imprecise input to yield output, fuzzy logic fits well with the nature of high uncertainty in geosciences data. The one-year study is conducted on reservoir basis using well monitoring results to split well level...

... operation casing design drilling fluid density Artificial Intelligence fuzzy logic casing and cementing risk assessment Engineering safe region target well xx5 drilling risk risk probability profile cycle cost risk treatment cost coordination mechanism risk management optimization problem...

... Index RQI, this paper addresses specifically the AI application to the different rock modals through Thomeer methodology. decision tree learning coefficient neural network decision tree model training crossplot fuzzy logic grid Artificial Intelligence fuzzy logic cluster cluster radius...

... of this technology needs strenuously considerable efforts in candidate-well selection. This paper presents a novel approach of candidate-well selection by combining fuzzy logic, gaussian membership function, multi-level grey correlation analysis, imperialist competitive algorithms with artificial neural networks...

... perform better. The use of an incorrect design can lead to serious over estimation of the P90, which must be avoided. geologic modeling reservoir characterization geological modeling fuzzy logic machine learning neural network experiment soft computing method factorial design optimal lhd...

..., % 48.4 21.7 20.0 6.6 3.3 Figure 8 Fuzzy-logic predicted permeability using cluster analysis – training Figure 9 Fuzzy-logic predicted permeability using cluster analysis – testing Figure 2 Scatter plot of core permeability versus core porosity Figure 3...

... with the fuzzy approximate matching rule, to realize quick and uncertain fuzzy reasoning [ 5 - 7 ]. The fuzzy expert system combines the advantages of the expert system itself and fuzzy logic, and does a decent job simulating the thinking of human experts, in solving problems of uncertain reasoning [ 6...

... as a separate layer of information. Integration of each of these layers was performed in fuzzy logic on the basis of the importance and dominance of each property. In cases where the reservoirs have been too close to one another, they have a mutual domain which has an unrealistic impact on the adjacent...

... contribution from individual reservoir layer is required for the field's reservoir simulation modeling and production evaluation/prediction. This paper presents an approach to solve the problem. The approach is basically based on the application of soft computing (Fuzzy Logic) to investigate pattern...

.... This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear...

... operation hydrate fuzzy logic reservoir surveillance reservoir simulation expert system production monitoring production control consideration gas hydrate related drilling risk molecule lattice flow assurance note thermal conductivity drill pipe selection drilling fluids and materials...

... is that it is based on sound physical principles of multiphase flow in porous media. Furthermore, heterogeneity can easily be incorporated into the model using geostatistical techniques. Artificial Intelligence (AI), such as fuzzy logic systems, artificial neural networks and expert systems, have been used...

... [11] the same Gassmann model is used, from which the two rock matrix dry properties as functions of porosity are produced after a good match with the observed data has been achieved. modeling estimation log data laboratory dynamic test well logging log analysis fuzzy logic elastic...

... intelligence reservoir engineer identification upstream oil & gas screening algorithm fuzzy learning vector quantization fuzzy logic expert system artificial intelligence technique engineer and artificial intelligence technique knowledge management society data mining flvq characterization...