Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Michael Andrew Christie"'
Publikováno v:
Computational Geosciences. 24:1725-1746
One way to quantify the uncertainty in Bayesian inverse problems arising in the engineering domain is to generate samples from the posterior distribution using Markov chain Monte Carlo (MCMC) algorithms. The basic MCMC methods tend to explore the par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::744a5e69a8678122e153ee5107757ca1
https://doi.org/10.1007/s10596-020-09968-z
https://doi.org/10.1007/s10596-020-09968-z
Publikováno v:
SPE Reservoir Evaluation & Engineering. 23:479-497
Summary The Todd and Langstaff (1972) mixing parameter (ω) is the most commonly used parameter in black oil reservoir simulators for modeling the effects of viscous fingering on a field scale, as their model is a useful alternative to compositional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56afb340835dd002e8f5f93ec4236dbe
https://doi.org/10.2118/185858-pa
https://doi.org/10.2118/185858-pa
Publikováno v:
Journal of Petroleum Science and Engineering. 175:444-464
In an uncertain oil price environment, brownfield redevelopment is becoming an increasingly attractive option to manage production decline. One of the essential strategies in brownfield redevelopment is optimally placing the infill well to maximize r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a67bdb5ca524a35c647ac0a5ea100f88
https://doi.org/10.1016/j.petrol.2018.12.043
https://doi.org/10.1016/j.petrol.2018.12.043
Publikováno v:
Mathematical Geosciences. 51:209-240
Bayesian uncertainty quantification of reservoir prediction is a significant area of ongoing research, with the major effort focussed on estimating the likelihood. However, the prior definition, which is equally as important in the Bayesian context a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47f38d5ebb4125a0a43217a45f04b080
https://doi.org/10.1007/s11004-018-9774-6
https://doi.org/10.1007/s11004-018-9774-6
Publikováno v:
Mathematical Geosciences. 51:241-264
Models used for reservoir prediction are subject to various types of uncertainty, and interpretational uncertainty is one of the most difficult to quantify due to the subjective nature of creating different scenarios of the geology and due to the dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d168edc982777dc70266d6257b4ed251
https://doi.org/10.1007/s11004-018-9755-9
https://doi.org/10.1007/s11004-018-9755-9
Publikováno v:
SPE Journal. 22:1296-1312
Summary Multiobjective history matching has gained popularity in the last decade. It provides an ensemble of diverse set and good matched models that should lead to improved forecasting. Moreover, in some cases, multiobjective history matching provid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cbe26ad69345a4ee086a2beda17a4fc
https://doi.org/10.2118/185957-pa
https://doi.org/10.2118/185957-pa
Publikováno v:
Computational Geosciences. 21:533-551
Different interpretation of sedimentary environments lead to “scenario uncertainty” where the prior reservoir model has a high level of discrete uncertainty. In a real field application, the scenario uncertainty has a considerable effect on flow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2350d0f12c695a7f3b5611487360e51d
https://doi.org/10.1007/s10596-017-9629-0
https://doi.org/10.1007/s10596-017-9629-0
Publikováno v:
Computers & Geosciences. 95:123-139
Assessing the change in uncertainty in reservoir production forecasts over field lifetime is rarely undertaken because of the complexity of joining together the individual workflows. This becomes particularly important in complex fields such as natur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1ca52e9ccd918d5ebc678c8c006d25c
https://doi.org/10.1016/j.cageo.2016.07.011
https://doi.org/10.1016/j.cageo.2016.07.011
Publikováno v:
Journal of Petroleum Science and Engineering. 190:107094
The current work illustrates the convergence properties of a Monte Carlo Simulation (MCS) used to quantify the geological uncertainty in reservoir simulation. We investigate the convergence behavior of MCS on 3D, 3-phase, highly heterogeneous reservo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc6e454ff5013582d76ab13f48965e68
https://doi.org/10.1016/j.petrol.2020.107094
https://doi.org/10.1016/j.petrol.2020.107094
Publikováno v:
Proceedings.
Summary The present work illustrates the convergence properties of a Monte Carlo Simulation (MCS) used to quantify the geological uncertainty in a 3D, 3-phase reservoir simulation test case. Our reservoir model along with fluid and numerical properti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6238d76dea0f6a075bb486f2d4156d41
https://doi.org/10.3997/2214-4609.201802226
https://doi.org/10.3997/2214-4609.201802226