Artificial Intelligence for Real-Time Monitoring of Fracture Driven Interactions and Simultaneous Completion Optimization

Autor: Alireza Shahkarami, Glen Murrell, Thomas Nguyen, Rob Klenner, Hayley Stephenson

Publikováno v: Day 3 Wed, September 30, 2020.

This paper builds on Klenner et al. 2018, which utilized machine learning to understand well-to-well communication ("Frac hits") or fracture-driven interaction (FDI) during hydraulic fracturing operations. This paper introduces an infrastructure that

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c557d39585053ccccf306879b3c91133
https://doi.org/10.2118/199967-ms

Utilizing Bayesian Optimization and Machine Learning to Find the Best Inflow Control Design for Horizontal Wells

Autor: Elena Meyer, Naresh Iyer, Alireza Shahkarami, Oscar Becerra Moreno, Glen Murrell, Meagan Friedrichs, Robert Klenner, Ghazal Izadi

Publikováno v: Day 1 Mon, May 04, 2020.

Inflow Control Devices (ICDs) help reduce the adverse consequences of uneven inflow issues in a lateral completion system. The most common uneven inflow consequences are early water breakthrough and gas coning in water-driven and saturated reservoirs

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38c4fb57a23dfa80c18c1d100e0f30c5
https://doi.org/10.4043/30716-ms

Accelerated Completion Optimization with Uncertainty Reduction Through Coupled Data and Physics Based Hybrid Models

Autor: Naresh Iyer, Nurali Virani, Glen Murrell, Hayley Stephenson, Alireza Shahkarami, Guoxiang Liu, Robert Klenner, Brian Chandler Barr

Publikováno v: Day 1 Tue, April 09, 2019.

Optimization problems, such as optimal well-spacing or completion design, can be resolved rapidly via surrogate proxy models, and these models can be built using either data-based or physics-based methods. Each approach has its strengths and weakness

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d820d2ff7bf6b153baa5531c162d1853
https://doi.org/10.2118/195238-ms

Characterization of Fracture-Driven Interference and the Application of Machine Learning to Improve Operational Efficiency

Autor: Rob Klenner, Naresh Iyer, Anveshi Charuvaka, Nurali Virani, Hayley Stephenson, Guoxiang Liu, Glen Murrell

Publikováno v: Day 2 Thu, September 06, 2018.

Frac hits are a form of fracture-driven interference (FDI) that occur when newly drilled wells communicate with existing wells during completion, and which may negatively or positively affect production. An analytics and machine-learning approach is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::71189aef20df1f5708dc9f4761f80b05
https://doi.org/10.2118/191789-ms

Unravelling a long-term multi-event thermal record in the cratonic interior of southern Finland through apatite fission track termochronology

Autor: Paul Andriessen, Glen Murrell

Publikováno v: Physics and Chemistry of the Earth, Part A: Solid Earth and Geodesy, 29(10), 695-707. Pergamon Press Ltd.
Murrell, G R & Andriessen, P A M 2004, ' Unravelling a long-term multi-event thermal record in the cratonic interior of southern Finland through apatite fission track termochronology ', Physics and Chemistry of the Earth, Part A: Solid Earth and Geodesy, vol. 29, no. 10, pp. 695-707 . https://doi.org/10.1016/j.pce.2004.03.007

Apatite fission track thermochronology (AFTT) has been applied to the Precambrian basement rocks of southern Finland in an attempt to detect within the long-term thermal history, thermal manifestations in the cratonic interior of tectonic events at t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e25049a48c1c730eeb03004c7076238
https://hdl.handle.net/1871/30495