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Keywords: accuracy
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Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0064
... with variable features (Whittaker et al., 1989; Kratzsch, 1983). fluid dynamics subsidence reservoir geomechanics geology geologist geological subdiscipline magnitude prediction calculation equation boundary formulation distance engineering romero benitez correspond accuracy agioutantis...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0056
... on a simple illustrative example, i.e., single-fracture propagation, are used to demonstrate the accuracy and efficiency proposed approach. The proposed deep-learning-based visualizations model should be a fast emulator for quantitative characterization and monitoring of hydraulic fracturing stimulation...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0035
... characteristic weibull scratch test reservoir geomechanics strength heterogeneity geologist rock type geological subdiscipline cst statistical fracture theory microcell texture correlation innovative combination shale compressive strength accuracy international journal defect ARMA 24 0035...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0096
... number of training samples). The research utilizes simulation data reflecting scenarios like single-phase, two-phase, and two-phase flow with mechanics inspired by the Illinois Basin Decatur Project. Results reveal that p-INO significantly surpasses conventional INO models in accuracy, particularly...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0095
.... Machine learning classification algorithms, including support vector machines (SVM), K-nearest neighbors (KNN), random forest, naïve Bayesian, extreme gradient boost (XGB), and neural networks, were employed. The SVM model demonstrated superior performance, achieving an accuracy and F1-score of 80.95...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0921
... conducted simulations to gather data to be able to study the potential of these algorithms to facilitate automatic monitoring and detect defects. The results indicate that machine learning can significantly enhance the predictive maintenance of thrust bearings, with XGBoost achieving a leading accuracy...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1007
... geomechanics machine learning tbm saalg geomechanics gemini algorithm workflow sensor operation accuracy excavation ground-related anomaly visualization tunnel tbm operation hydraulic tunnel santos incidence application ARMA 24 1007 GEMINI, a novel software system to improve...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1057
...-time surface hole GR by leveraging drilling parameters and mud weight data. Training on datasets from six wells with a total of 2,100 data set yielded accurate predictions, with the ANN model slightly surpassing ANFIS in performance. The models were and assessed for accuracy using metrics such as root...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1085
... ABSTRACT: Estimating Shale Volume using conventional methods in the Bakken formation, a complex heterogeneous reservoir, is challenging due to the presence of other radioactive minerals. This study aims to evaluate the accuracy of several machine-learning algorithms in predicting shale volume...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0976
.... This implies spending several hours of highly skilled engineers doing this routine task. Changing to an unsupervised classification method, based on AI, has shown an extremely high overall accuracy (as high as 0.97 over the validation dataset), allowing to perform the database filtering on real time while...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1136
... and extensive training, the model achieved a prediction accuracy of 90%, closely matching actual field data. 1 INTRODUCTION 1.1 Purpose And Significance Of The Paper Hydraulic fracturing technology is an important method for enhancing production and injection in oil and gas well production...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0132
... the training of ROP models and degrade their accuracy. In this paper, a methodology for handling anomalous data is proposed based on oilfield drilling data. Firstly, isolated forest (IF) detection is employed to identify and remove outliers, followed by the application of K-nearest neighbor (KNN) interpolation...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0201
... structure. geologist rock type sedimentary rock structural geology machine learning fracture information accuracy study reservoir characterization porosity imaging diameter zhang artificial intelligence registration fib-sem characteristic resolution pore subsample journal...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0187
... sets to establish a deep neural network model. Finally, the obtained mud leakage probability model is applied in BZ block. The research shows that the accuracy of the model trained by training data with correlation degree [0.2, 1) is 78.2%, and the prediction accuracy of this model is the highest...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0279
.... Despite only achieving an accuracy of 29.6% on the testing dataset, the model shows promising improvement towards the desired shape after only 100 epochs of training. Potential approaches for improvement, such as integrating error distributions into the analysis and employing a training→prediction...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0189
... the casing pressure and bottom hole flow pressure production data, we derived a comprehensive calculation model for determining the depth of fluid accumulation in both the tubing and annulus. The accuracy of the model was validated through on-site assessments involving flow pressure, static pressure...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0209
... the best model with the highest performance. The machine learning algorithms include Decision Tree (DT), Support Vector Machine method (SVM), and Artificial Neural Networks (ANNs). The best accuracy of the different models is 90.91% (DT), 72.7% (SVM), and 87.5% (ANNs). The data that we have collected...
Proceedings Papers

Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0231
... in mineral identification. However, the scale of the log data is more than eight cm per point, and more than the accuracy of the logging data is needed for fine formation analysis. Therefore, this paper proposes an adaptive image segmentation method for predicting elastic parameters based on large thin...

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