... portal drone construction malaysia orthophoto integration gcp representation requirement elevation aerial 360 information revolutionizing construction stakeholder remotely piloted aircraft system accuracy model Introduction Let’s first delve into the background and its connection...

... of the Pareto front that connects all solutions of the multi-objective optimization, this preparation stage not only provides important search directions for the subsequent multi-objective optimization, but also improves the accuracy of the surrogate model near the Pareto front. The second stage...

... formula to improve the search speed and optimization accuracy of the algorithm; finally, Levy flights are introduced into the warning position updating formula to avoid local optimality. Comparison experiments are done between the Sparrow Search Algorithm (SSA), Particle Swarm Optimization Algorithm (PSO...

... control workflow digital twin historian shutdown reservoir surveillance real time system offshore technology conference accuracy proactive approach Introduction In the dynamic landscape of oil and gas exploration and production, the challenges associated with flow assurance have become...

.... Our experimental results demonstrate that the detected leak rates exhibit an accuracy exceeding 78%. By employing this deep learning image processing model, natural gas extraction systems can significantly enhance their ability to detect gas leaks promptly, reducing revenue losses and mitigating...

... and gas industry. choke valve drillstem/well testing artificial intelligence drillstem testing completion equipment reservoir surveillance machine learning application information dataset production control algorithm bk-s3-n limitation accuracy incident prediction flow coefficient...

... accuracy dataset Where, ρ m is the density of the gas-liquid mixture (kg/m 3 ); f m is the friction factor (dimensionless); z is depth (m); ν m is the velocity of the gas-liquid mixture (m/s); D is the diameter of tube (in). (4) v m = v s g + v s l = v g α...

... In this binary lithology classification assessment, the model demonstrated notable performance in distinguishing between shale (Class 0) and sand (Class 1) can be observed in Fig. 3 . The model achieved an accuracy of 89%, indicating its effectiveness in correctly classifying instances from both...

... in an offshore shale oil field in South China Sea, and the digital prediction results were compared with actual downhole pressure tests and manual interpreted results with a good and satisfactory accuracy. This confirms the effectiveness, reliability, and efficiency in transforming domain knowledge and data...

... vs actual has illustrated the prediction of the thickening time with an average accuracy of 83% confirmed by the model box plot. The model validation consisted of employing a set of data to predict the thickening time for more than 11 slurries with an average absolute error of 6%. Model...

... associated with hydrate formation and corrosion. These investigations often rely on the use of software modeling tools, and ensuring the accuracy of the model's parameters is of utmost importance. Key model parameters in relation to hydrate and corrosion risk include water solubility and hydrate dissociation...

..., the interpretation of the results, and the value gained from the surface data acquisition form the survey results and way forward proposals. valve co 2 well wellhead artificial lift system axis gas-lift mandrel gas lift mandrel accuracy gas-lift injection injection data acquisition surveillance...

... then be generated. geology machine learning geologist casing and cementing artificial intelligence prediction cbi seismic velocity tvdss despiking accuracy cement and bond evaluation dataset reservoir geomechanics algorithm geological subdiscipline balancing fcnn hoopstress xyoffset cement...

... maintaining measurement accuracy. The presence of hydrate formation, scale deposition, and other flow assurance issues in subsea well operations can complicate the task of maintaining the precision of the measurements. Physical MPFMs have the following challenges associated with their deployment...

... for trajectory prediction are based on models with numerous assumptions, limiting their simultaneous applicability. Moreover, some existing machine learning algorithms overlook the impact of drilling modes (sliding or rotating) and Bottom Hole Assembly (BHA) types, necessitating improvements in their accuracy...

... provides a methodology for assessing estimation algorithms and a scenario for deploying machine learning techniques to reliably forecast the condensate RVP for a production facility. Several RVP prediction approaches are used to evaluate the accuracy and field optimization prospects. Machine learning...

... Abstract For an already established 3D geologic model, the accuracy of model correction only by seismic and well data is not high. Seismic-driven modeling, a modeling method that fully integrates seismic data, can fully explore the potential information in seismic data and convert seismic...

... efficiency, power and fuel gas consumption of the fleet. The model is then utilized in a mathematical optimization algorithm and the optimized data used for training and validation of a Random Forest Regressor model. The performance model in Python is able to achieve accuracies of <1% absolute error when...

... learning deep learning automatic fault segmentation neural network accuracy artificial intelligence fault location segmentation information reservoir characterization upstream oil & gas wavelet cnn model training process cnn model technology conference subsurface fault wavelet...

..., from the subsea industry first applications 20 years ago. controls and umbilicals subsea processing accuracy application electrical industrial apparatus upstream oil & gas actuation system requirement artificial intelligence subsea battery operation actuator battery electronics...