..., pore pressure prediction, in-situ stress regime, and presence of faults and fractures. The study will also investigate the relationship between in-situ stress, fractures, faults distributions, and fluid flow and correlate fracture properties variations to the lithology changes. The results from...

... for economic and other practical reasons. We propose to accurately predict these types of log data from the traditional common types of well log measurement data using deep sequence learning methods. After anomalous data removal and augmenting the ratio DTC/DTS as a new lithology differentiating feature...

... casted precisely to the given shape and dimensions. Conducted lab experiments confirmed the theoretically predicted superiority of notches over holes in reducing fracturing pressure. Introduction In certain geomechanical settings of today’s increasingly complex tight reservoirs, initiating hydraulic...

... Abstract The objective of this paper is to highlight a new machine learning application to predict a synthetic caliper log using other available Logging While Drilling (LWD) well logs. LWD logs and wireline (WL) mechanical caliper logs for 17 tight gas wells, with more than 120,000 depth data...

... elkatatny journal mahmoud drilling fluids and materials log analysis prediction abdelaal pressure gradient estimation Abstract Real-time estimation of the formation pressure can enhance the drilling operations in terms of non-productive time, costs, and safety. In the literature, the known...

... consumption, it can supply its energy demands for the next 100 years. reservoir characterization prediction upstream oil & gas vaca muerta shale argentino vernik argentina basin estimation buenos aire correlation important unconventional argentinian play stiffness bower reservoir...

... calculation shows how an incomplete or poorly interpreted dataset may be misleading, thereby highlighting the inherent uncertainties and difficulties associated with borehole stability modelling. wellbore integrity mohr-coulomb orientation borehole wellbore design criteria plane prediction...

...-order Padé-type thermoelastic constants derived by the approximation of Padé rational function to the total strain energy. The Padé thermoelastic constants are characteristics of a reasonable theoretical prediction for acoustic velocities of solid rocks even at high temperature. The results demonstrate...

... advantages. This feature is important in highly urbanized areas where usable land is scarce and acquiring land can put high financial pressure on available budgets. Tunnelling uncertainty is the main contributor to cost overruns which are mainly due to geological uncertainity. Therefore, accurate prediction...

... algorithm machine learning upstream oil & gas sand control prediction completion installation and operations sand/solids control random forest hyperparameter sand control completion technique k-nearest neighbor nait amar supervised ml algorithm artificial intelligence selection...

... learning k-means experiment coefficient prediction data mining algorithm knowledge symposium dataset Abstract Formation drillability evaluation plays an essential role in the exploitation of shale gas reservoirs. Currently, the common methods for evaluating formation drillability mainly...

... Abstract An accurate prediction of elastic parameters is crucial for predicting minimum horizontal stress in wellbore stability, drilling design of horizontal borehole azimuth and hydraulic fracturing in petroleum engineering. For a transversely isotropic shale formation, the vertical...

...ARMA/DGS/SEG International Geomechanics Symposium 21 0021 In-situ stresses prediction by using a CNN-BiLSTM-Attention hybrid neural network Tianshou Ma*, Guofu Xiang State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan, China...

...ARMA/DGS/SEG International Geomechanics Symposium 21 60 Comparison and Validation of Analytical and Numerical Sand Production Prediction Methods with Core Tests and Field Sanding Data Khaksar, A., Asadi, M.S. and Younessi. A. Baker Hughes, Perth, WA, Australia Copyright 2021 ARMA, American Rock...

...ARMA/DGS/SEG International Geomechanics Symposium 21 601 Sonic Logs Prediction in Real Time by Using Random Forest Technique Hany Gamal, Ahmed Alsaihati, Salaheldin Elkatatny*, and Abdulazeez Abdulraheem College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals...

... machine learning hydraulic fracturing correlation artificial intelligence upstream oil & gas flow in porous media fluid dynamics reservoir characterization complex reservoir oil production reservoir pressure porosity prediction effective stress stress-dependent permeability...

... the algorithm and used later to validate the built models. These data cover different types of formations, carbonate, sandstone and shale. A good match between the actual and predicted Young’s modulus was achieved with correlation coefficients above 0.92 and average absolute percentage errors were less than 15...

... ABSTRACT: The prediction of the pore pressure is significant mainly for drilling. It can improve the quality of decisions and the drilling economics. The offered models in the literature for pressure prediction are based on well logs or a combination of some drilling data and well logs...