... & gas artificial intelligence information ml algorithm productivity accuracy machine learning automated detection method validation interaction energy economics fracture dependent interaction unconventional resource technology conference frac operation supervised learning algorithm urtec...

... models due to advantages in handling time series data. Accuracy of model predictions was validated by ground truth data. This work showcases an example of using both physics-based and data-driven modeling to maximize value from optimizing production and operations. For the first time, the mechanism...

... infrastructure and the well pads. Overall, the MPFM reduced the investment cost needed for ancillaries (space, power, manifolds, etc) and improved safety by reducing fugitive and Scope 3 emissions without compromising measurements accuracy. In every respect the MPFM provided a far better value for the operator...

... that the approach can estimate pore pressures with the same or greater accuracy as traditional pore pressure prediction methods and to do so at the drill bit, in near real time. Introduction Traditional pore pressure estimation while drilling utilizes a combination of data sources most of which are detected...

... events are crucial for high fracturing efficiency. The current human-made methods for identifying fracturing events are time-consuming with low accuracy, and unable to provide real-time warning of various fracturing events. In order to improve the efficiency of fracturing decision-making, this work...

... by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any...

... forecast united states government complex reservoir production monitoring energy economics mape urtec upstream oil & gas artificial intelligence machine learning information presented reservoir surveillance canada government technology conference accuracy unconventional...

... of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any information obtained from this paper...

... dataset accuracy huff-n-puff injection diffusion coefficient average error complex reservoir rock type artificial intelligence machine learning prediction algorithm engineering gas injection shale gas reservoir characteristic urtec adsorption mudstone injection recovery factor...

... simulation datta-gupta united states government modeling & simulation evolutionary algorithm accuracy unconventional reservoir fracture engineering multi-resolution multi-well unconventional reservoir simulation Abstract This study aims to develop a rapid workflow that combines a multi...

... Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information...

... accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility...

... complex reservoir unconventional play refracturing geology completion hydraulic fracturing proppant united states government machine learning accuracy petroleum play type unconventional resource technology conference energy economics refrac completion figure haynesville paper distribution...

... learning accuracy algorithm unconventional resource technology conference upstream oil & gas deep learning artificial intelligence information history hydrocarbon production behavior hyperparameter reservoir utilizing deep learning model URTeC: 3863926 Predicting Hydrocarbon Production...

... reservoir characterization deep learning complex reservoir artificial intelligence upstream oil & gas machine learning neural network accuracy repeatability rf hybrid xgb xgb hybrid powder river basin prediction workflow model result petrophysicist xgb xgb hybrid best result...

.... The highest performance for a single well prediction using the ML models with an R 2 value of 99.90%. In a deep neural network, Bi-LSTM performs superior with an accuracy of 92.5%. The highest average accuracy obtained for single well prediction is 90.7%. Cross well prediction performed superior for all...

... be cost prohibitive. In summary, measurement challenges include: • Infrequent tests due to: ∘ Measurement system cost ∘ Measurement system portability • Measurement system accuracy ∘ Measurement errors may be due to measurement system sizing and changing flow rates from the well • Lack...

... reservoir characterization shale gas machine learning artificial intelligence upstream oil & gas anisotropy parameter well logging structural geology variation stiffness coefficient total porosity dipole sonic log accuracy prediction input rock property geophysics wolfcamp...

... in Oklahoma. The trained model was then tested against an unseen dataset of 47 recent Ovintiv wells in Oklahoma and performed with a 96% total classification accuracy. The results indicate that SWD injection rate, SWD location, SWD surface pressure, drilling fluid density, and interferometric synthetic...

... because of the complex string motion state in real wellbores and limited considering factors in physical model. Machine learning features in high dimensional process modelling and large volume of data processing, it's possible to increase the accuracy of T&D prediction during drilling by combining...