... structural geology decision tree learning accuracy hypothesis application classification experiment machine learning lithology rhob nphi validity threat log analysis canada government precision evaluation metric prediction accuracy automatic identification reservoir characterization...

... consumed products. Across five years of predictions (2016 to 2019), the models were able to predict with 78% average accuracy for the top 10 products by volume which represents 75% of inventory volume. Across the same time-period, they were able to predict with 73% average accuracy on all 17 products which...

... reaches the minimum drilling time for an area, C3: Constant reflecting the idealized minimum drilling time for the area. Defining the value of the three constants; C1, C2, and C3, is the most critical step in the process as it affects the accuracy of the total duration predications for future wells...

... data (frac, cement bond logs), and pre-production testing data (choke, pressure etc.) Initial results indicate that this approach is a feasible approach, on target in terms of accuracy with traditional methods and represents a novel, data driven, method of identifying optimal parameter settings...

... in all possible flow conditions with acceptable accuracy in a single multiphase meter. As a summary, the data-driven VFM is a computational operator that relates X to the entries of vector Y . (1) X ( t ) → V F M Y ( t ) . This operator is initially obtained during...

... 98 Support Vector Machine 21 2 4 126 Random Forest 22 1 3 127 For the ANN model, 1000 runs were conducted. The accuracy was relatively high, as shown in Fig. 2 . There was also a good fit with a minimal gap...

... gradient boost, Gradient boost regressor and Linear regressor) and a deep learning algorithm (Artificial Neural Network). The output results from the set of supervised learning algorithms and Deep Learning algorithms were compared in terms of their accuracies in predicting the hydrate formation...

... the inventory issue. Therefore, it is desirable to reduce workover time and optimize production by providing early warning of ESP failures ( Fig. 1 ). artificial lift system neural network artificial intelligence machine learning deep learning accuracy information electrical submersible pump...

.... The model was validated using unseen data set (1,000 data points) of Well (B), which is located in the same field and drilled across the same complex lithology. The results showed the high performance for the model either for training and testing or validation processes. The overall accuracy for the model...

... and measured points by tuning the "L factor." This procedure cannot ensure that the resulting model will satisfy other production tests at different flowing conditions, which reveals the difference between accuracy and consistency. In contrast, the present effort suggests a practical approach for better...

... and usability of rig sensor data. Focus is on gains/kick events in particular. The calibration algorithm analyzes the quality of sensors in a mud circulation system and calibrates these sensors to yield meaningful data. This leads to a much higher accuracy in the sensed data, e.g. by mitigating flow sensor...

... accuracy. More complicated models employ ensemble techniques which can be computationally robust and provide excellent accuracy. When ensemble techniques are used, identifying the data associated with each method can be crucial to efficiency of the technique. The data used in an ensemble technique...

... transmitted to surface using the mud pulse system for real time QC and processing vertical seismic profile accuracy downhole tool real time processing Upstream Oil & Gas depth prognosis pipe Reservoir Characterization wireline vsp real time velocity update real time positioning real time...

..., and random forests (RF) are used to predict ROP. Trees provide easy interpretability and hence are favored over other non-linear techniques. However, accuracy is imperative in this procedure. Accuracy can be increased by using bootstrap aggregating (bagging) or Random Forests. These techniques are applied...

... operated and eventually need to be abandoned. An integrated tool covering an entire lifecycle of an instruments existence is required for an effective management. Challenges Instruments have increased role as industries strive for efficiencies in business processes and increased accuracies...