... technology, machine learning study on production data have emerged, such as Fully Connected Neural Network (FCNN) and Recurrent Neural Network (RNN)( Wang et al ., 2020 ), etc. In addition, the commonly used reservoir numerical simulation methods are time consuming, and the history matching accuracy greatly...

... into the ML model. For a dataset of approximately 18,000 reservoirs with high confidence in the recovery factor, a model was developed with 6 numerical features. The model exhibited an accuracy of ±5% for 50% of the data (between P25 and P75) and ±10% for 80% of the data (between P10 and P90). Contrary...

... automation. A project analysis comparing use of CF++ vs. conventional work processes was completed to determine improvement in speed, quality and cost. The paper will present savings in speed, cost and accuracy by comparing CF++ outputs against the manual process deliverables from out turn projects. CF...

... dramatically reducing risk and intervention time. experiment information machine learning operation upstream oil & gas algorithm correlation simulator experimentation equation perception scenario simulation artificial intelligence digital twin model accuracy constraint representation...

... reports and then were analyzed and ranked to identify the most important parameters on the performance and accuracy of the model utilizing advance algorithm and correlation analysis. This is to predict and classify test measurement via the utilization of a non-linear relationship through the use of data...

.... upstream oil & gas saudi aramco saudi arabia government asia government artificial intelligence pdt machine learning process digital twin grossmann optimization operation application accuracy knowledge neural network data mining constraint dashboard simplification implementation...

... this approach is based on data and algorithms, the potential exists for improving efficiency and accuracy. In a case study, data from 130 existing horizontal wells in the Ordos tight oil field were collected for analysis. These data included logging data, well engineering parameters, and production performance...

... work done by Tengizchevroil (TCO) specialists on the calibration of existing IM, it became possible to forecast the field production with a deviation of up to 1% from the actual one. The authors conclude that in order to achieve high forecast accuracy in IM, data consistency between all model elements...

...) and a challenging level of resolution of measurement from test to test on the same wells (3-5%). The actual accuracy of the measurements can vary depending on the rates and the flowing conditions at the separator. Permanently installed test separator, with a test manifold that allows to align one well at a time...

... upstream oil & gas well logging oilfield structural geology log analysis interpretation artificial intelligence lithology reservoir performance application coefficient society seismic inversion petroleum engineer accuracy optimization method inversion reservoir...

...-to-reach environments. upstream oil & gas artificial intelligence anomaly encode dataset machine learning architecture anomaly detection neural network detection toyadmos dataset experiment contrastive learning algorithm contrastive learning deep learning accuracy algorithm...

... illustration workflow artificial intelligence prediction module neural network smartvessel incident layout violation operation protective equipment hse use-case classifier comprehensive ai-based safety monitoring solution accuracy Introduction 100%-HSE culture is one of the main drivers...

... was close to one, indicating high performance. Structured querying on the knowledge graphs also showed high accuracy for classifying anomalous events in the drilling report. The work described in this paper automates the end-to-end workflow for building an expert system for answering questions about...

... Emission transducers installed between the test section and software to collect and filter the data. The technology has been deployed on one Feed Condensate pipeline back in 2020/21 with continuous data collection. Higher accuracy was achieved comparing against latest intelligent pigging (IP) data...

... Layer Perceptrons, Sequence to sequence modelling, Long short term memory models and finally transformers are employed for the improvement of accuracy of patent reactions. The paper presents detailed comparative results of predicting chemical reaction yield, and the enhancements that it will bring...

... of consistency and level of accuracy of more than 80%. The result of this work is an ML classification model that can reduce daily morning report data entry by 40% and improve the operational classification quality and consistency significantly. This approach also improves internal processes such as services...

... and benchmarked technically and commercially against completed LNG projects, both internal and external company, with inclusion of one's corporate memories, to increase the predictability of the model. Post internal and external benchmarking analysis, the accuracy of the model is within the anticipated range...

... integrity patera upstream oil & gas reactor physics-based structural digital twin accuracy refinery simulation application deviation approximation INTRODUCTION The age-old question of how to do more with less is ever prevalent in today's macro and microeconomic environment. Industrial...

... the drilling process, they are also required to determine the position of the well with sufficient accuracy to enable the drilling of a relief well in the event that loss of well control occurs, and also to enable updating of the subsurface model. Abstract The well-collision-avoidance management...

... (or organic-rich) thin beds, and their mechanical properties. In general, rapid enhanced resolution processing of the acquired acoustic waveforms contributes to the accuracy of FE at the very early stages. It can also be beneficial to assist in adjusting the logging strategy (Formation testing, sampling...