... was trained/tested to predict K r curves in the absence of P c curves as an input. The performance of the three developed models (XGB, DNN, and RNN) was assessed using the values of the coefficient of determination ( R 2 ) along with the loss calculated during training/validation of the model. The respective...

.... As a result, how to combine a variety of data to avoid data islands and identify and predict the space of fracture zone is of great importance. In this paper, we present a method and workflow based on the microseismic (MS) data combined with shear wave velocity data to estimate the physical parameters...

...M. V. Behl; M. Tyagi Summary Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, large gridblock counts simulation is computationally expensive and time-consuming. This study explores data-driven reduced-order models (ROMs...

... for history matching and future prediction by INSIM-BHP with those from a high-fidelity commercial reservoir simulator. Results show that INSIM-BHP yields accurate forecasting of wells' oil rates and BHPs on a daily level even under the influence of oscillatory rate schedules and changing operational...

... estimates. This work evaluates the predictive accuracy of rate-time models to forecast production from tight-oil wells using Bayesian methods. We apply Bayesian leave-one-out (LOO) and leave-future-out (LFO) cross-validation (CV) using an accuracy metric that evaluates the uncertainty of the models...

... polymer flood performance. However, the performance of the lower layers of Mangala (FM-3 and FM-4) continued to progressively deviate from modeling estimates. Importantly, the observed polymer breakthrough deviated significantly from predictions. As the polymer flood matured, the trend of field water cut...

...Toluwalase Olukoga; Micheal Totaro; Yin Feng Summary This paper investigates the computational behaviors of simple-to-use, relatively fast, and versatile machine learning (ML) methods to predict apparent viscosity, a key rheological property of nanoparticle-surfactant-stabilized CO 2 foam...

...Leding Du; Yuetian Liu; Liang Xue; Guohui You Summary Oilfield development performance prediction is a significant and complex problem in oilfield development. Reasonable prediction of oilfield development performance can guide the adjustment of the development plan. Moreover, the reservoir...

... is scrutinized far less often than horizontal permeability ( k x , k y ) in most geological and reservoir modeling. However, our work indicates that it is equally important to understand k z characteristics to better evaluate their influence on CO 2 EOR and storage performance prediction. We conducted this study...

... correspond machine learning wellbore integrity reservoir simulation upstream oil & gas information high-resolution model stress solution subvolume spe reservoir evaluation coarse model mechanical properties stress field november 2021 fracture gradient finite-element solution prediction...

...Hui-Hai Liu; Jilin Zhang; Feng Liang; Cenk Temizel; Mustafa A. Basri; Rabah Mesdour Summary Prediction of well production from unconventional reservoirs is often a complex problem with an incomplete understanding of physics and a considerable amount of data. The most effective way for dealing...

... and efficiency of the developed model. The respective crossplots indicate that the model is capable of making accurate predictions with an error percentage of less than 2% on history matching experimental data. This implies that the artificial-intelligence- (AI-) based model is capable of determining K r and P c...

... are applied in conjunction with DCA models to estimate DCA parameter prediction intervals. Using these prediction levels, production is forecasted, and uncertainty bounds are established. To examine its reliability, the methodology was tested on over 74 oil and gas wells located in the three main subplays...

...Tao Yang; Gulnar Yerkinkyzy; Knut Uleberg; Ibnu Hafidz Arief Summary In a recent paper, we published a machine learning method to quantitatively predict reservoir fluid gas/oil ratio (GOR) from advanced mud gas (AMG) data. The significant increase of the model accuracy compared to traditional...

...Wendi Liu; Svetlana Ikonnikova; H. Scott Hamlin; Livia Sivila; Michael J. Pyrcz Summary Machine learning provides powerful methods for inferential and predictive modeling of complicated multivariate relationships to support decision-making for spatial problems such as optimization of unconventional...

...Kachalla Aliyuda; John Howell; Elliot Humphrey Summary Predicting oilfield performance is extremely challenging because of the large number of variables that can influence and control it. Traditional methods such as decline‐curve analysis have been commonly used but have been shown to have...

...Lichi Deng; Yuewei Pan Summary Closed‐loop reservoir management (CLRM) consists of continuous application of history matching and optimization of model‐predictive control to maximize production or reservoir net present value (NPV) in any given period. Traditional field‐scale implementation of CLRM...

...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...

... distribution for steamflood reservoir management purposes (Hong 1994 ; Nath et al. 2007 ). In addition to FLT, wellhead temperature (WHT) is another surface temperature. Predicting the long‐term WHT trend in steamflood operation is necessary for designing surface facilities for both oil dehydration/separation...

... to visualize vaporizing/condensing phenomena at the oil/gas interface using a visualization cell. Finally, we use the measured CCE and MMP data to calibrate the Peng-Robinson (Robinson and Peng 1978 ) equation of state (PR‐EOS) and predict the MMP of the oil/gas systems using ternary diagrams. The results...