... analyses for a long period of time. AAHCR is a very strong synthetic parameter giving a direct indication of the peak temperature value before, during, and after the in-situ combustion (ISC) front is generated. Therefore, it provides complete information on the occurrence of high-temperature oxidation...

...) as an alternative to detailed physics-based simulations. ROMs that use neural networks (NNs) effectively capture nonlinear dependencies and only require available operational data as inputs. NNs are usually labeled black-box tools that are difficult to interpret. On the other hand, physics-informed NNs (PINNs...

...., injection or production fluid) and specific environment (e.g., geological strata or compartments). A comparative analysis of the microbial profiles suggested possible well connectivity and water breakthrough. These results demonstrate that microbial DNA-based monitoring can provide useful information...

... monitoring production control node spe reservoir evaluation evolutionary algorithm perforation upstream oil & gas optimization problem reservoir surveillance machine learning information reynolds imaginary node paper prediction model aquifer node texas simulator equation Closed...

... information. For example, Zhu and Zabaras (2018) used grid blocks of reservoir properties as inputs to perform image-to-image regression, predicting pressure maps in heterogeneous reservoirs using a convolutional encoder-decoder. Another application was by Mo et al. (2019) where a convolutional encoder...

... but cannot be fulfilled by deterministic solvers. Stochastic Bayesian methods have been applied to assess the uncertainties, but the high run time, tedious parameter tuning, and need for specific prior information hinder their practical use. We implement Markov chain Monte Carlo with ensemble samplers...

... network reservoir prediction machine learning matrix ag-gru wavelet coefficient permeability engineering numerical simulation software graph sensitivity matrix artificial intelligence information lstm ad-gcn In each waterflooding reservoir ( Zhang et al. 2016a ), oil/water dynamic...

... of the information from 23 wells was investigated using the MVA workflow aiming at identifying the key factors that affect the production performance in the study area. The MVA workflow reveals the weak correlation between production and legacy well effect. The results show that the key factors affecting production...

... ). The core idea of the GCN is to use edge information to aggregate node information and finally generate a new node representation. The generation of graphs is a key step of the GCN. If the graph structure cannot well encode the correlation between nodes, the GCN will not be able to accurately extract...

... (for example, it is so coarse that it has only one cell), it would not capture any relevant information. Please note that in what follows, an asterisk will be used to denote quantities in the coarse scale. For instance, E , ν and E * , ν * will denote the stiffness and Poisson’s...

...K. Chawshin; A. Gonzalez; C. F. Berg; D. Varagnolo; Z. Heidari; O. Lopez Summary X-ray computerized tomography (CT) is a nondestructive method of providing information about the internal composition and structure of whole core reservoir samples. In this study we propose a method to classify...

... to determine the desirability of a project for a company (expected utility). Quantitative decision analysis, including a value of information (VoI) calculation, can be done addressing the uncertainty range but also the risk hurdles as required by the decision‐maker (DM). The next step is the development...

...Abdulaziz Almansour; Stephen E. Laubach; J. Eric Bickel; Richard A. Schultz Summary A core‐based fracture prediction method is used to illustrate a value‐of‐information (VOI) decision‐analysis protocol to inform completion decisions in tight gas sandstones. The ratio of late host‐rock cement...

... this information to improve future estimation procedures; investors, who can analyze reported reserves estimates to compare volumes fairly; and regulators, to whom the paper provides quantitative methodology to suggest to filers to help them ensure compliance with appropriate criteria for 1P and 2P reserves...

... ability to retain information in a form of memory of previous patterns and information contained in the previous behavior of phenomena being modeled. This memory plays a role of informing the decision at the present time by using what happened in the past. This property suggests the RNN as a suitable...

... Upstream Oil & Gas reservoir manager criterion steam-assisted gravity drainage geological uncertainty utility function SPE Reservoir Evaluation realization SSD SDR decision support system information machine learning asset and portfolio management reservoir simulation flow simulator...

... the assumptions considered in classic Kriging, it is realistic to assume that spatial data contain a certain amount of imprecision, mostly because of measurement errors, and information is lacking to properly assess a unique random‐function model. A methodology is presented for the geostatistical estimation...

.... The value‐of‐information (VOI) framework, which is a powerful decision‐analysis tool, provides an estimate of the value of learning. Closed‐loop reservoir management (CLRM) is considered to be a state‐of‐the‐art approach to solving for the optimal IOR switch time. However, the CLRM approach can produce...

...Egbadon Udegbe; Eugene Morgan; Sanjay Srinivasan Summary In recent years, there has been a proliferation of massive subsurface data sets from sources such as instrumented wells. This places significant challenges on traditional production‐data‐analysis methods for extracting useful information...

... injection, laboratory experiments have to be performed, and a pilot project might be required before field implementation. The decision to perform a pilot project can be dependent on a value‐of‐information (VOI) calculation. The VOI can be derived by performing a work flow that captures the effects...