... manual labeling is not sufficient for model training. For the other five alarms, the workflow uses an Edge-enabled physics-based flowrate calculation to flag the status of different alarm categories. The presented workflow innovatively combines machine-learning algorithms with rule-based criteria...

... Processing (NLP) has been developed as a dedicated branch of artificial intelligence to build machines that understand and respond to text or voice data in much the same way as humans do. NLP algorithms offer the best possibility to address the described business needs managing issues related to the written...

... . demonstrate the distribution of petrophysical properties in both oil fields. Machine Learning Algorithms for Chemical Treatment Prediction Feature Generation The given dataset provided information about the well treatment process with the help of varied physical and geographical data. Further, we...

.... Industry literature review was performed to determine parameters of ultra-deep tools, investigate their responses, and add them to the list of supported devices. Inversion algorithm is based on stochastic Monte Carlo method with reversible jump Markov chains and can be launched automatically without prior...

... engineer limited-budget project algorithm database production data management system Introduction This workflow was developed for production engineering group exploiting a mature oilfield in the Oriente basin, Ecuador. This field started its production in 2002 and reached a production peak...

... learning approach to evaluate the performance of the DA. The model was constructed using four different algorithms: MLP, SVC, RF, and AdaBoost, with each model evaluated and compared using five evaluation indicators. Furthermore, a feature importance analysis was conducted to assess the contribution...

... multiple imaging sensors spaced at known distances. The sensors capture images of the same formation location at different but synchronized times. The method includes an image-matching algorithm that identifies each image's fingerprint and registers similar images according to those fingerprints...

.... The technology and algorithm were developed using extensive data collected through full-size prototype laboratory testing. A test fixture simulating a wellhead system was constructed to collect digitalsignatures of various scenarios of hanger landings and packoff settings at carefully controlled offsets from...

... corrosion artificial intelligence frequency defect voltage transmitter inductance scenario simulation inspection flowline corrosion prediction sensor coil subsystem well integrity coil machine learning diameter coupling dimension defect depth defect location algorithm pixel accuracy...

... tools are applied before training the models to eliminate the XRD data outliers due to the formation complexity. The algorithms are based on well logs as inputs such as Gamma Ray, bulk density, neutron porosity, resistivity, and photoelectric factor for seven (07) wells. XRD mineral components for 117...

.... A correlation was formulated between permeability and the NCS to illustrate the stress dependency relationships. The Grey Wolf Optimization algorithm (GWO) was used to tune the correlation for the Bakken formation. Machine Learning methods were also applied for the porosity and permeability stress dependency...

... by setting α = 0. Abstract Previous implementation of distributed Gauss-Newton (DGN) optimization algorithm runs multiple optimization threads in parallel, employing a synchronous running mode (S-DGN). As a result, it waits for all simulations submitted in each iteration to complete, which may...

... Among a large number of algorithms available for the data assimilation problems, ensemble Kalman-based methods receive special attention as it provides a robust solution to the history matching problem for various types of reservoir modeling applications ( Aanonsen, et al. 2009 , Perrone et al...

... optimization algorithm that is designed specially to promote the accuracy of a kernel-based proxy model for robust production optimization. In our study, we consider a least-squares support vector regression (LS-SVR) which is also briefly reviewed here. Stochastic Simplex Approximate Gradient (StoSAG)-Based...

... guided by a smart sampling algorithm. Proxy models are trained and validated by feeding the training datasets to supervised machine learning algorithms. Lastly, the tested proxy models are run for a multi-parameter sensitivity study for design optimization. The workflow was validated by a Marcellus...

... to offset wells. To calculate FBHP, production engineers use physics-based models and empirical correlations calibrated with actual physical measurements from offset wells. The objective of the paper is to develop a data driven approach for prediction of the FBHP with machine learning algorithms during post...

... to 100% to reach the system autonomy requirement. This article highlights four major cornerstones for building such a system: Initialization data validation Static and continuous survey filtration Robustness of the key algorithms QC of output data and system operation. The cornerstones...

... intelligence psia machine learning regressor predictor prediction neural network lightgbm algorithm coefficient artificial proxy feature dew point pressure reservoir temperature relative error dataset upstream oil & gas correlation elsharkawy pseudocritical property kennedy molecular...

... (labels) in a set of training wells in the same field and/or region. Our ML model of choice for predicting the desired properties is the decision tree-based learning algorithm called random forests (RF). We also devise a mechanism to automatically tune the hyperparameters of this algorithm depending...

... to efficient stringer drilling presented here is a consistent, timely and reliable method of detecting stringers. This is enabled by a fit for purpose stringer detection algorithm embedded in a measurement-while-drilling (MWD) tool for vibration and load measurements, combined in a systems approach...