... and better decision-making [ 3 ] artificial intelligence knowledge management innovation training program natural language digital dexterity efficiency platform employee deep learning machine learning digital dexterity initiative citizen developer data mining digital transformation...

... operations. data mining accuracy artificial intelligence arima and linear regression model material reservation linear regression model future material reservation deep learning machine learning filter forecasting forecasting accuracy supply chain management ai model sample output root...

... sustainability complex reservoir asset and portfolio management reservoir surveillance production monitoring geological subdiscipline geologist reservoir simulation project economics artificial intelligence sustainable development machine learning business ethics deep learning social responsibility...

... obviously in subtle fault identification. By integrating the fault orientation information provided by FMI logging, sensitive azimuths of seismic data were chosen for different subtle faults. AI subtle fault identification method based on deep learning can analyze large volumes of seismic diffraction...

... geologic model geo-conditioned gan deep learning neural network transitional environment delta environment stratigraphy depositional environment geological subdiscipline facies co 2 application facies model gan-generated model reservoir modeling conditioning data simulation information...

... production enhancement well intervention production chemistry hydrate remediation wax remediation scale sample scale deposition scale inhibition asphaltene remediation completion installation and operations wax inhibition scale remediation ann model sulfate scale deep learning mineral...

.... During the recent years, artificial intelligence (AI) solutions have become widely adopted in the oil and gas industry and geology. Data science algorithms and deep learning models have empowered tools capable of rapid analysis and extracting insights from geological, geophysical and production data...

... mean square error (RMSE) reduced from 522.87 to 382.15, demonstrating a significant enhancement in the model's prediction accuracy and performance. Incorporating water cut as a constraint variable into the deep learning prediction strategy significantly improves GOR curve trend accuracy...

... Abstract This study focuses on leveraging deep learning method, specifically Convolutional Neural Network (CNN), to enhance seismic data interpretation for mapping karst bodies in Central Luconia carbonate platform, offshore Sarawak, Malaysia. The research aims to improve the accuracy...

... dynamics in the oil and gas industry, facilitating more precise reservoir characterization and informed decision-making in field development and management. geologist artificial intelligence deep learning reservoir characterization porosity prediction information sequence geology well...

... artificial lift system artificial intelligence module esp well production data chengdu northern petroleum exploration management module section electric submersible pump symposium deep learning machine learning exploration and development technology co current pattern china zhenhua oil co...

... to manual methods. natural language deep learning artificial intelligence contract machine learning invoice data source llm integration contract management tool unstructured data extraction application large language model agent database optionality analysis use case energy company...

... deep learning drilling fluid property reservoir geomechanics collapse pressure parameter uncertainty wellbore stability structural geology drilling fluids and materials drilling fluid selection and formulation prediction result coordinate system maximum horizontal principal stress...

... properties such as fluid saturation, pore pressure, and more. geologist artificial intelligence structural geology outcrop deep learning reservoir characterization neural radiance field leveraging neural radiance field digital outcrop reconstruction and characterization nerf dataset...

... an efficient and scalable approach for CO2 storage forecasting. geology geologist deep learning artificial intelligence subsurface storage reservoir characterization enhanced recovery prediction climate change saturation mae co2 storage forecasting accuracy injection location neural...

... complex reservoir systems. simulation deep learning machine learning artificial intelligence reservoir management engineer computational efficiency decision-making experimental data generative ai model ar interface natural language efficiency accuracy pore-scale fluid flow...

... casing and cementing riser corrosion corrosion machine learning deep learning artificial intelligence flowline corrosion corrosion classification utilizing machine learning engineer subsurface corrosion materials and corrosion algorithm ml model category well integrity neural...

... language. These models are built upon deep learning architectures, particularly transformer architectures, and are trained on vast amounts of text data from the internet. They have the capability to perform a wide range of natural language processing (NLP) tasks, such as text generation, translation...

... drilling operations, leveraging the present condition of wells. drilling operation machine learning artificial intelligence large language model deep learning accuracy llm ddr extraction traditional method classification information text data natural language dataset data augmentation...

...) and the Gate Filtering Model (GFM). The AIM uses traditional machine learning to recognize known anomaly patterns and deep learning to spot complex, subtle discrepancies using real-time surface data such as bit depth, hole depth, hook load, block position, stand pressure, flow rate, RPM, and torque. The GFM...