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Roland N. Horne
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Proceedings Papers

A Data-Driven Approach for Stylolite Detection

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Jingru Cheng, Bohao He, Roland. N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214831-MS
https://doi.org/10.2118/214831-MS
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View Paper titled, A Data-Driven Approach for Stylolite Detection
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Proceedings Papers

Simulating Multiphase Flow in Reservoirs with Generative Deep Learning

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Abdullah A. Alakeely, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 21–23, 2021
Paper Number: SPE-206126-MS
https://doi.org/10.2118/206126-MS
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View Paper titled, Simulating Multiphase Flow in Reservoirs with Generative Deep Learning
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Proceedings Papers

Application of Deep Learning Methods in Evaluating Well Production Potential Using Surface Measurements

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Abdullah A. Alakeely, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, October 26–29, 2020
Paper Number: SPE-201785-MS
https://doi.org/10.2118/201785-MS
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View Paper titled, Application of Deep Learning Methods in Evaluating Well Production Potential Using Surface Measurements
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Journal Articles

Simulating the Behavior of Reservoirs with Convolutional and Recurrent Neural Networks

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Abdullah Alakeely, Roland N. Horne
Journal: SPE Reservoir Evaluation & Engineering
Publisher: Society of Petroleum Engineers (SPE)
SPE Res Eval & Eng 23 (03): 0992–1005.
Paper Number: SPE-201193-PA
https://doi.org/10.2118/201193-PA
Published: 13 August 2020
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View articletitled, Simulating the Behavior of Reservoirs with Convolutional and Recurrent Neural Networks
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Proceedings Papers

Simulating the Behavior of Reservoirs with Convolutional and Recurrent Neural Networks

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Abdullah Alakeely, Roland N. Horne
Paper presented at the International Petroleum Technology Conference, January 13–15, 2020
Paper Number: IPTC-20191-MS
https://doi.org/10.2523/IPTC-20191-MS
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View Paper titled, Simulating the Behavior of Reservoirs with Convolutional and Recurrent Neural Networks
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Journal Articles

Applying Machine-Learning Techniques To Interpret Flow-Rate, Pressure, and Temperature Data From Permanent Downhole Gauges

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Chuan Tian, Roland N. Horne
Journal: SPE Reservoir Evaluation & Engineering
Publisher: Society of Petroleum Engineers (SPE)
SPE Res Eval & Eng 22 (02): 386–401.
Paper Number: SPE-174034-PA
https://doi.org/10.2118/174034-PA
Published: 14 January 2019
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View articletitled, Applying Machine-Learning Techniques To Interpret Flow-Rate, Pressure, and Temperature Data From Permanent Downhole Gauges
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Proceedings Papers

Recurrent Neural Networks for Permanent Downhole Gauge Data Analysis

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Chuan Tian, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, October 9–11, 2017
Paper Number: SPE-187181-MS
https://doi.org/10.2118/187181-MS
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View Paper titled, Recurrent Neural Networks for Permanent Downhole Gauge Data Analysis
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Proceedings Papers

Inferring Interwell Connectivity Using Production Data

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Chuan Tian, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 26–28, 2016
Paper Number: SPE-181556-MS
https://doi.org/10.2118/181556-MS
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View Paper titled, Inferring Interwell Connectivity Using Production Data
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Journal Articles

Physical Mechanisms Related to Microseismic-Depletion-Delineation Field Tests With Application to Reservoir Surveillance

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Jack H. Norbeck, Roland N. Horne
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 21 (04): 1279–1288.
Paper Number: SPE-178926-PA
https://doi.org/10.2118/178926-PA
Published: 15 August 2016
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View articletitled, Physical Mechanisms Related to Microseismic-Depletion-Delineation Field Tests With Application to Reservoir Surveillance
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Journal Articles

Detecting Fracture Growth Out of Zone by Use of Temperature Analysis

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Priscila M. Ribeiro, Roland N. Horne
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 21 (04): 1263–1278.
Paper Number: SPE-170746-PA
https://doi.org/10.2118/170746-PA
Published: 15 August 2016
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View articletitled, Detecting Fracture Growth Out of Zone by Use of Temperature Analysis
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Proceedings Papers

Compositional Variation Study for Improving Recovery in Gas-Condensate Reservoirs

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Hai X. Vo, Roland N. Horne
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, August 1–3, 2016
Paper Number: URTEC-2458783-MS
https://doi.org/10.15530/URTEC-2016-2458783
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View Paper titled, Compositional Variation Study for Improving Recovery in Gas-Condensate Reservoirs
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Proceedings Papers

Experimental Study of Composition Variation During Flow of Gas-Condensate

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Hai X. Vo, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 28–30, 2015
Paper Number: SPE-175011-MS
https://doi.org/10.2118/175011-MS
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View Paper titled, Experimental Study of Composition Variation During Flow of Gas-Condensate
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Proceedings Papers

Machine Learning Applied to Multiwell Test Analysis and Flow Rate Reconstruction

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Chuan Tian, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 28–30, 2015
Paper Number: SPE-175059-MS
https://doi.org/10.2118/175059-MS
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View Paper titled, Machine Learning Applied to Multiwell Test Analysis and Flow Rate Reconstruction
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Proceedings Papers

Development of a General Likelihood Maximization Method for Robust Parameter Estimation from Pressure Transient Data

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Parag Bandyopadhyay, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 28–30, 2015
Paper Number: SPE-175003-MS
https://doi.org/10.2118/175003-MS
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View Paper titled, Development of a General Likelihood Maximization Method for Robust Parameter Estimation from Pressure Transient Data
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Proceedings Papers

Applying Machine Learning Techniques to Interpret Flow Rate, Pressure and Temperature Data From Permanent Downhole Gauges

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Chuan Tian, Roland N. Horne
Paper presented at the SPE Western Regional Meeting, April 27–30, 2015
Paper Number: SPE-174034-MS
https://doi.org/10.2118/174034-MS
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View Paper titled, Applying Machine Learning Techniques to Interpret Flow Rate, Pressure and Temperature Data From Permanent Downhole Gauges
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Proceedings Papers

Detecting Fracture Growth Out of Zone Using Temperature Analysis

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Priscila M. Ribeiro, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, October 27–29, 2014
Paper Number: SPE-170746-MS
https://doi.org/10.2118/170746-MS
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View Paper titled, Detecting Fracture Growth Out of Zone Using Temperature Analysis
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Proceedings Papers

Modeling Adsorption of Gases in Nanoscale Pores Using Grand Canonical Monte Carlo Simulation Techniques

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Maytham I. Al Ismail, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, October 27–29, 2014
Paper Number: SPE-170948-MS
https://doi.org/10.2118/170948-MS
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View Paper titled, Modeling Adsorption of Gases in Nanoscale Pores Using Grand Canonical Monte Carlo Simulation Techniques
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Proceedings Papers

An Investigation of Gas-Condensate Flow in Liquid-Rich Shales

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Maytham I. Al Ismail, Roland N. Horne
Paper presented at the SPE Unconventional Resources Conference, April 1–3, 2014
Paper Number: SPE-169021-MS
https://doi.org/10.2118/169021-MS
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View Paper titled, An Investigation of Gas-Condensate Flow in Liquid-Rich Shales
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Proceedings Papers

Pressure and Temperature Transient Analysis: Hydraulic Fractured Well Application

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Priscila M. Ribeiro, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 30–October 2, 2013
Paper Number: SPE-166222-MS
https://doi.org/10.2118/166222-MS
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View Paper titled, Pressure and Temperature Transient Analysis: Hydraulic Fractured Well Application
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Proceedings Papers

Interpreting Pressure and Flow Rate Data from Permanent Downhole Gauges with Convolution-Kernel-Based Data Mining Approaches

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Yang Liu, Roland N. Horne
Paper presented at the SPE Annual Technical Conference and Exhibition, September 30–October 2, 2013
Paper Number: SPE-166440-MS
https://doi.org/10.2118/166440-MS
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View Paper titled, Interpreting Pressure and Flow Rate Data from Permanent Downhole Gauges with Convolution-Kernel-Based Data Mining Approaches
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