... to production performance prediction and fracturing optimization. hydraulic fracturing fracture length reservoir characterization upstream oil & gas microseismic event identification artificial intelligence orientation fracture network tracer flowback profile fracturing fluid machine...

... failure date. These findings enable gas operators to arrange the maintenance and replacement of the pumps, reducing the downtime and thereby increasing the production of gas wells. artificial lift system complex reservoir artificial intelligence machine learning queensland detection control...

... time series in tight reservoirs due to changes in flow regimes. machine learning upstream oil & gas information artificial intelligence schmidhuber deep learning high noise prediction lstm prediction neural network physics-constrained prediction low noise international conference...

... and its connectivity back to the wellbore. The new method does not require any well surveillance compared with existing methods and does not incur extra cost to operator. production control real time system reservoir characterization artificial intelligence complex reservoir production...

...×10 4 m 3 /day after the appropriate shut-in treatment. The study results provide a scientific basis for the optimization of shut-in-time for the development of similar shale gas reservoirs. optimization problem shale reservoir multi-fractured horizontal well artificial intelligence...

... production data gas content history-matching artificial intelligence coal seam gas es-mda statistics data assimilation bowen basin coal bed methane complex reservoir convergence ensemble posterior ensemble permeability realisation history-matched ensemble static property smoother initial...

... depletion state well spacing complex reservoir future development well sector model resource density solution space artificial intelligence decision framework model well spacing study ranking methodology section subsurface realisation scenario machine learning upstream oil & gas value...

... samples with various total organic contents origins and mineralogy. The study illustrates the capability of the artificial intelligence and neural network modeling to predict adsorption capacity on aforementioned shale samples utilizing various scope matrixes. The study can provide useful Information...

.... machine learning artificial intelligence fracturing materials chemical flooding methods hydraulic fracturing enhanced recovery proppant regression np-co2 foam fracturing fluid ml algorithm algorithm machine learning model reservoir conditions rmse support vector regression neural network...

... geomechanics production monitoring production logging artificial intelligence hydraulic fracturing complex reservoir multistage fracturing completion installation and operations perforation diameter proppant fracture characterization open cluster net pressure spe annual technical conference...

.... It is the belief of the authors that the application should work in any basin globally. When combined with an automated choke systems and artificial lift the APD application can be expanded to field wide optimization. artificial intelligence rate measurement error production history real time system...

... and operation, and enhance the potential of shale reservoir development. shale gas net pressure index satisfy eq fracture propagation mode artificial intelligence upstream oil & gas shale gas fracture network fracturing fracture network complexity fracture machine learning complex reservoir...

... to the stress reorientation in a multi-layer shale reservoir. The results from the numerical studies provide more instructive suggestions on infill drilling of highly fractured reservoirs. artificial intelligence hydraulic-natural fracture intersection natural fracture density upstream oil & gas...

.... neural network artificial intelligence complex reservoir machine learning drilling operation deep learning correlation rop in-seam drilling drill bit engineering formation type gamma ray noncoal gamma ray log machine learning model xgboost coal noncoal classification regression task...

... it was completed? How to quantify, separately, the contribution of completion and location to production? Can sweet spots be identified in an area using production data? Does completion effectiveness vary with location, or operator, or year? artificial intelligence machine learning hydraulic fracturing...

... constraints into DL models. equation of state pvt measurement artificial intelligence deep learning constraint calculation machine learning reservoir simulation thermodynamic constraint rachford-rice equation composition physics fraction dl model phase mole fraction prediction mole...

... process parameter morphology artificial intelligence upstream oil & gas pore structure co 2 shale gas complex reservoir adsorption micropore adsorption capacity clay mineral padmanabhan shale sample engineering isotherm natural gas science uptake URTEC-208386-MS The Effective...

... classification. artificial intelligence segmentation reservoir characterization deep learning machine learning neural network pixel information technology services upstream oil & gas arxiv preprint arxiv seismic data wall-clock time u-net facies classification dataset seismic facies...

... estimates. We present the application to production data of tight-oil wells building an average predictive distribution for the estimated ultimate recovery (EUR). machine learning production forecasting complex reservoir bayesian bootstrap model uncertainty artificial intelligence upstream oil...

... networks. In addition to life-cycle decision-making, stimulation design, the prediction of compaction and subsidence, and reservoir management can all benefit from the knowledge gained in this study. reservoir geomechanics hydraulic fracturing wellbore design artificial intelligence coal seam gas...