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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208298-MS
...URTEC-208298-MS Using Machine Learning for Geosteering During In-Seam Drilling Ruizhi Zhong, Ray L. Johnson Jr, and Zhongwei Chen, The University of Queensland Copyright 2021, Unconventional Resources Technology Conference (URTeC) DOI 10.15530/AP-URTEC-2021-208298 This paper was prepared...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208320-MS
... fracturing fracture network complexity fracture wellbore propagation bedding fracture net pressure index machine learning complex reservoir hydraulic friction coefficient operation pressure curve pressure curve Copyright 2021, Unconventional Resources Technology Conference (URTeC) ...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208275-MS
... depletion state well spacing machine learning upstream oil & gas value driver complex reservoir future development well solution space sector model resource density artificial intelligence decision framework model well spacing study ranking methodology section subsurface realisation...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208310-MS
... in subsurface rocks. However, the rigorous thermodynamics approach to obtain phase composition (based on a given pressure, temperature, and overall mole fraction) is computationally expensive. So, various researchers have considered using machine learning models trained with the rigorous phase-equilibrium...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208309-MS
...URTEC-208309-MS A Machine Learning Approach to Benchmarking: A New Perspective Utilizing Factor Contribution Analysis Hamed Tabatabaie, Toby Burrough, and Camilo Rodriguez Cadena, IHS Markit Copyright 2021, Unconventional Resources Technology Conference (URTeC) DOI 10.15530/AP-URTEC-2021-208309...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208315-MS
... pad assessments. 2 URTEC-208315-MS Using readily available hydraulic fracturing treatment data, completion and reservoir engineers and geoscience teams obtain meaningful results accelerating the learning curve and are provided a large parametric population for multivariant analysis and machine...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208348-MS
... intelligent decision method for predicting the AOFP is considered to be a win-win strategy for gas recovery as well as economic performance. In this study, one of the most classic unsupervised machine learning methods namely, principal component analysis (PCA), was combined with radial basis function neural...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208376-MS
... be drawn as follows: 1. Based on a large number of data points collected from literature, a comprehensive database is generated, which is helpful to analyze and verify various models to predict the onset of liquid loading. A future promising application of the database can be resorted to the machine...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208350-MS
... by the method, which lays a theoretical foundation for the establishment of development modes of diversified low permeability carbonate reservoirs in the Middle East. flow in porous media reservoir characterization upstream oil & gas fluid dynamics machine learning oilfield microscopic pore...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208367-MS
... machine learning upstream oil & gas well-to-well log correlation real time system artificial intelligence information log analysis litho-fluid interpretation drilling parameter data scientist operational geologist geological area application operation algorithm well logging...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208313-MS
... upstream oil & gas complex reservoir mineralogy impact adsorption machine learning regression accuracy variation correlation svr method padmanabhan testing data matrix artificial intelligence adsorption measurement information coefficient shale sample methane adsorption...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208394-MS
... obtained from this paper does so at their own risk. The information herein does not necessarily reflect any position of URTeC. Any reproduction, distribution, or storage of any part of this paper without the written consent of URTeC is prohibited. Abstract The rise of modern machine learning has inspired...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208389-MS
... petrophysicists and engineers with many different specialties, including drilling, completions, reservoir, and numerical simulation. Also, enter the newcomers but very important specialists: Geoscientists and engineers with abilities in machine learning (ML) and data analytics (DA). All these statistical...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208344-MS
... geomorphology, channel boundaries, and faults might not be fully visible, resulting in misleading labeled data and incorrect interpretations. Hence, in this work, we propose the application of 3D machine learning models to solve the problem of seismic facies classification. This introduces a two-fold challenge...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208400-MS
... to production performance prediction and fracturing optimization. hydraulic fracturing fracture length reservoir characterization upstream oil & gas machine learning complex reservoir fracture cluster artificial intelligence orientation fracture network sweet spot fracture identification...
Proceedings Papers

Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208406-MS
... 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 machine learning upstream oil & gas progressing cavity pump early...

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