1-20 of 50
Keywords: neural network
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196577-MS
.... Neural network models are trained to learn the key performance impacting factors on shale gas production in a dynamic manner, which could assist reservoir management decisions. complex reservoir artificial intelligence machine learning shale gas upstream oil & gas neural network model kpi...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196608-MS
... variables, Neural Network models are then developed to study the impacts of all parameters on gas production as well as perform history matching of the field history. The AI assisted model with acceptable matching of field data can be used to model different hydraulic fracturing design scenarios and provide...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196598-MS
... engineers to recognize flow patterns and estimate reservoir properties. We demonstrated the versatility and applicability of our proposed approach with synthetic and field cases. pressure transient analysis neural network pressure transient testing diagnostic plot proceedings Production analysis...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196614-MS
... modifications are also presented. Both standard and machine learning techniques were used to analyze the results. neural network vertical permeability calculation machine learning reservoir simulation cutoff simulator flow in porous media fluid dynamics simulation heterogeneous model...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191823-18ERM-MS
... operations and handling of extremely large data bases, hence, facilitating tough decision-making processes. machine learning google patent node Artificial Intelligence Exhibition algorithm prediction probability neural network dataset information operation decision tree automation...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191827-18ERM-MS
... Vector Machines (SVMs), Artificial Neural Networks (ANNs), and Gaussian Processes (GP)) were applied to understand the non-linear patterns in the data. The objective was to develop predictive models that were trained and validated based on the current database. The predictive models were validated using...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 4–6, 2017
Paper Number: SPE-187516-MS
... (c) shape of rock inclusions (i.e., grains and pores). Core measurements are used for cross validating the well-log-based estimates of elastic moduli and petrophysical properties. Accordingly, we proposed a rock classification technique using unsupervised neural network that integrated depth-by-depth...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 4–6, 2017
Paper Number: SPE-187511-MS
... optimization problem drilling operation neural network numerical reservoir simulation model complex reservoir Upstream Oil & Gas hydraulic fracturing Directional Drilling simulation model performance forecast artificial neural network NPV Shahkarami drilling scenario drainage area society of...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 4–6, 2017
Paper Number: SPE-187514-MS
... of different groups of parameters such as reservoir characteristics, operational activities on the ultimate recovery determination in shale gas reservoir. production monitoring neural network information production control complex reservoir cumulative production Reservoir Surveillance...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, September 13–15, 2016
Paper Number: SPE-184064-MS
... pressure), and operational constraints (well-head pressure) on the EUR calculated by each of the DCA techniques. The question we are trying to answer is whether the use of a particular DCA technique translates into the emphasis of a certain group of parameters. Artificial Intelligence neural network...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 13–15, 2015
Paper Number: SPE-177318-MS
... design parameters in a given shale asset. As the first step CDC-EUR is estimated. In the second step data-driven analytics using artificial neural networks is employed to condition the CDC-EUR to rock properties, well characteristics, and completion design parameters. Then, artificial Intelligence...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 21–23, 2014
Paper Number: SPE-171003-MS
... process knowledge. This model can be used for a variety of purposes such as optimization, prospect evaluation, underperforming wells, and evaluating completion/frac methods. This process is demonstrated in Figure 4 . Figure 4 Neural network (ANN) modeling workflow. Developing any...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 3–5, 2012
Paper Number: SPE-161184-MS
... & gas calibration machine learning hydraulic fracturing modeling individual well shale reservoir model neural network reservoir model data mining hydrocarbon production optimum history society of petroleum engineers history production rate history matching completion marcellus shale...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 13–15, 2010
Paper Number: SPE-139101-MS
... network training with previously identified parameters. Training of neural networks is performed with around 80% of the database, while the rest of the data is used for training quality estimation (calibration and verification). Training is repeated with different combinations of inputs, until predicting...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, September 23–25, 2009
Paper Number: SPE-125959-MS
... in this analysis is a synthetic reservoir with characteristics representative of a coal in the Appalachian Basin. All the reservoir simulation is performed using a commercial reservoir simulator (3). Artificial Intelligence complex reservoir coal bed methane neural network coalbed methane...
Proceedings Papers

Paper presented at the SPE Eastern Regional/AAPG Eastern Section Joint Meeting, October 11–15, 2008
Paper Number: SPE-117765-MS
... then, performs particle swarm optimization (PSO) to refine the results. The data conversion scheme is implemented by a neural network ensemble using the EC-PSO-derived LD outputs as training targets. This method has better capability to tackle problems of local minima and to produce robust conversion...
Proceedings Papers

Paper presented at the SPE Eastern Regional/AAPG Eastern Section Joint Meeting, October 11–15, 2008
Paper Number: SPE-117762-MS
... compositional, dual-porosity reservoir simulation model. A set of representative design scenarios is created and run using this model. Then, the collected performance indicators are fed into the neural network for training and two neural network-based proxies are developed: A forward proxy to predict the...
Proceedings Papers

Paper presented at the SPE Eastern Regional/AAPG Eastern Section Joint Meeting, October 11–15, 2008
Paper Number: SPE-119935-MS
... SPE 119935 Development and Testing of an Expert System for Coalbed Methane Reservoirs Using Artificial Neural Networks K. Srinivasan and T. Ertekin, Pennsylvania State University Copyright 2008, Society of Petroleum Engineers This paper was prepared for presentation at the 2008 SPE Eastern...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 11–13, 2006
Paper Number: SPE-104571-MS
... methodology includes an easy to use interface that allows the user to edit the data for a gas storage field, perform well-test analysis and use neural networks in association with Genetic optimization tool. The software ranks the well according to maximum change in skin value and recommends the best...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, September 14–16, 2005
Paper Number: SPE-98012-MS
.... A synthetic seismic model is developed by using real data and seismic interpretation. In the example presented here, the model represents the Atoka and Morrow formations, and the overlying Pennsylvanian sequence of the Buffalo Valley Field in New Mexico. Generalized regression neural network (GRNN...

Product(s) added to cart

Close Modal