...-to-use tool to automatically detect stuck pipe accurately and early. Based on the in-depth theoretical analysis and historical stuck pipe data analysis, main early stuck pipe indicators during different drill operations are identified. More than ten time series analysis algorithms and machine learning...

... model with high interpretability was developed to evaluate the response of CO 2 -EOR processes using random forest (RF) to maximize performance. The feature importance and interaction analyses were conducted to enhance the interpretability of RF model from global to local levels. The genetic algorithm...

... inversion methods. Yoshioka et al. (2007 and 2009 ) developed a microthermal effect-considering temperature prediction model, integrating it with the Levenberg-Marquardt (L-M) algorithm to create a DTS-based inversion model. This model has been successfully applied in interpreting flow profiles in mine...

... crossing. This paper summarizes the current methods for the detection of kick event, the study and the findings from replay of historical kick alarm cases, the methods of calibrating pit volume during drilling operation, the algorithms for rig state detection, and the application of early kick detection...

... points incorporating data attributes such as completion data, cumulative production from the same reservoir zone, and reservoir properties. To ensure accuracy, the dataset is split into an 80:20 ratio for training and validation purposes. The Decision Tree machine learning algorithm is selected...

... machine learning algorithm. The evaluation indexes of injection performance are established by integrating dynamic production data, such as injection-production ratio, water consumption rate, water cut, injection intensity, daily oil production capacity. According to the evaluation indexes...

... innovations in business processes, application of design thinking methodology, agile development, and AI. The AI waterflood management solution combines cloud technologies, big data processing, data analytics, machine learning algorithms, robotics, sensors and monitoring system, automation, edge gateways...

...-consuming. This paper introduces an automated approach using computer vision and random forest algorithms to streamline the process, providing a more efficient method for noise reduction, multi-level thresholding, machine learning (ML) model training, and application to SEM images for quartz overgrowth...

... efficiency engineer remote compressor performance platform flowline implementation productivity asia government algorithm compressor workflow database simulation operator Introduction In a typical offshore operation, optimization problems for wells and remote compressors are complicated...

... immensely. The benefits include minimization or reduction of costs associated with testing requirements, curtailed production, as well as the minimization of emissions. drillstem/well testing algorithm production control asia government reservoir surveillance well testing requirement drillstem...

... heterogeneous reservoirs with thin thickness. Furthermore, the geostatistical inversion combines Bayesian inference with a sampling algorithm called Markov Chain Monte Carlo (MCMC) that allows incorporating all the information from well logs, geological information, geostatistical parameters, and seismic data...

... of the parameters is completed by minimizing the fitness function from the loss between proxy model and measured data with the help of optimization-based algorithm. The new method is validated against numerical simulation, covering a wide range of fluid properties and operation constraints. upstream oil...

... candidate oil wells will be carried out with this technology in a later phase of the project. This Artificial Intelligence based High GOR Well Control (acronym iGOR), technology encompasses the following. Design of a real time well GOR control system based on smart algorithm. The control solution...

... is to predict synthetic caliper using logging while drilling (LWD) measurements (notably azimuthal density and petrophysical properties) with the help of artificial intelligence (AI) and machine learning algorithms that can be used in place of wireline caliper data thereby saving rig and logging costs and hence...

... permeability inflation coefficient development planning condensate reservoir ahm workflow localization algorithm Introduction The Ichthys gas-condensate field is located approximately 220 km offshore Western Australia in the Browse Basin, North West Shelf of Australia. Gas and condensate...

... importance to the different ML algorithms, we needed a rapid prototyping approach, and we finally opted for the use of "low-code" libraries which aided not only the latter but also simplified deployment of the final model. We will also highlight the importance of the training data to the predictive power...

... & gas permeability flow in porous media reservoir characterization neural network machine learning prediction xgboost springbok sandstone queensland australia accuracy algorithm fluid dynamics artificial intelligence surat basin ann classification journal rock permeability score...

.... liquefied natural gas data mining gas monetization artificial intelligence start-ups knowledge midstream oil & gas lng machine learning node mche novel application flowrate advisory harnessing tacit knowledge operator liquified natural gas tacit knowledge algorithm invaluable tacit...

... for continuous update of validated weight data in Module 1, and eventually improve & enhance capability of both the EDA and Predictive module. Using a supervised machine learning algorithms, the identified target variables were observed to provide weight prediction between 16% to 38% of Mean Absolute...

... challenge for modern communication algorithms. While multiple-Input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) communication has been extensively implemented in wireless communication for signal processing, unique challenges arise in subsurface reservoirs caused by unknown...