1-20 of 116
Keywords: machine learning
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, November 2–3, 2021
Paper Number: SPE-201786-MS
... integration of production, completion, subsurface and spatial data using machine-learning algorithms to predict production performance for future development wells. The internal Marcellus Business Unit (MBU) well database, populated with data of 500+ historical wells, has been used in this study. Production...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, November 2–3, 2021
Paper Number: SPE-201808-MS
... drilling operation machine learning fracturing materials shale gas complex reservoir oil shale knowledge management structural geology lateral length stage length fracturing fluid unconventional resource economics information reservoir geomechanics shale oil proppant wellbore design...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196572-MS
... brittleness along a borehole is an important step when deciding the right zones to fracture and for avoiding high injection gradients causing fracture formation during fluid injection processes. We have been successful in using machine learning methods for prediction of geomechanical properties...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196576-MS
... artificial intelligence data distribution inverse problem production data machine learning upstream oil & gas information regularization confidence interval standard deviation arp decline parameter probability distribution reservoir bayesian inference posterior distribution noise...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196577-MS
... 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 analysis spe eastern regional meeting reservoir simulation gas production shale gas production parameter...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196595-MS
...-established practice, a significant amount of analysis on their performance is focused on one or two key variables. The present paper adds to the existing body of literature by using data analytics and machine learning to evaluate this strategy from a truly multivariable standpoint. The paper also provides...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196613-MS
... a significant role in determining the success of hydraulic fracturing treatments. We have also compared the performances of supervised machine learning algorithms in assessing the impact of rock properties on fracturing treatments. Such supervised machine learning algorithms can help integrate field legacy data...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196608-MS
... production. artificial intelligence neural network shale gas reservoir shale gas upstream oil & gas numerical simulation database cumulative gas production machine learning complex reservoir simulation mohaghegh spe reservoir scenario hydraulic fracturing neural network model...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196597-MS
... be very problematic for weak formation, causing those formations to fracture. Although turbulent flow provides efficient hole cleaning, it is harmful to the weak formations and may cause many drilling problems ( Bourgoyne et al., 1986 ; Moore, 1986 ). machine learning drilling fluid chemistry well...
Proceedings Papers

Paper presented at the SPE Eastern Regional Meeting, October 15–17, 2019
Paper Number: SPE-196598-MS
... pressure transient analysis neural network pressure transient testing diagnostic plot proceedings Production analysis unconventional reservoir matrix form machine learning Upstream Oil & Gas deconvolution pressure response pressure map matrix permeability Artificial...
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
... to identify hidden patterns and help mitigate drilling challenges. Traditional data preparation and analysis methods are not sufficiently capable of rapid information extraction and clear visualization of big complicated data sets. Due to the petroleum industry's unfulfilled demand, Machine Learning (ML...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191827-18ERM-MS
... of these completion parameters? And how can we maximize the rate return on our investment? This study proposes innovative tools that allow researchers to answer these questions. We build these set of tools by utilizing the pattern recognition abilities of machine learning algorithms and public data from...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191779-18ERM-MS
... such as numerical simulation, machine learning, and linear programming. The essence of field development and optimization is to use completions design, as well as well spacing, to optimize the net present value of the field based on current commodity pricing, capital expenditure, operating cost, cycle time, and net...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191785-18ERM-MS
... modeling machine learning Upstream Oil & Gas bottomhole gauge data child well fracture proppant Drillstem Testing communication marcellus well parent well Artificial Intelligence drillstem/well testing frac stage statistical analysis roc curve Completion Operation frac production...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191788-18ERM-MS
... that applies time series statistics to modeling and forecasting of well production rates. A few studies have applied time series statistics (ARIMA modeling) to production ( Ayeni and Pilat 1992 ; Ediger et al. 2006 ; Yusof et al. 2010 ). Machine learning offers another source of improvement beyond decline...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191793-18ERM-MS
...., giving operators a risk-based analysis of prospective sites. We also made this analysis available to the public in a user-friendly web app. machine learning Artificial Intelligence Upstream Oil & Gas flow rate production monitoring shale gas Duong Marcellus Shale production control...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191794-18ERM-MS
... ridge regression interpretability machine learning regression correlation prediction exploratory plot annular pressure drop MSE dimensionality society of petroleum engineers predict pressure drop principal component pl regression principal component analysis predictive feature pearson...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191819-18ERM-MS
... under consideration include biocide type and concentration, fracturing fluid chemical additives, produced water reuse during completions, produced water chemistry, and geologic variation. Initial findings will be discussed and shared with lessons learned from production operations. machine...
Proceedings Papers

Paper presented at the SPE/AAPG Eastern Regional Meeting, October 7–11, 2018
Paper Number: SPE-191806-18ERM-MS
... Intelligence principal component machine learning Upstream Oil & Gas shale gas principal component score Monte Carlo model statistical learning method tw area geologic dataset petrophysical property workflow complex reservoir HCA principal component analysis production data unsupervised...

Product(s) added to cart

Close Modal