... enhanced recovery concentration permeability production control climate change journal engineering reservoir surveillance chemical flooding methods machine learning ch 4 mechanism shale gas co 2 reservoir geomechanics geological subdiscipline saturation reaction sequestration diffusion...

... class is assigned to the given image. By reducing the amount of data needed, the methodology enables quick extension of the existing workflow to previously unseen equipment. machine learning classification neural network triplet artificial intelligence cnn classifier dataset inspection...

... industry foundation llm annotation deep learning machine learning rag hallucination dataset preliminary research retrieval-augmented generation beijing petroleum exploration artificial intelligence fine-tuning corpora similarity median accuracy question-answer pair oil and ga industry...

... production control machine learning production monitoring classification geologist lwd well logging drilling measurement acquisition boundary optimizing image logging acquisition section lwd image log lwd image profile category precision recall accuracy evaluation metric image profile class...

... as opposed to fully descriptive models. With the integration of machine learning, these models have garnered increasing research interests recently. However, many existing reduced-order modeling methods, such as embed to control (E2C) and embed to control and observe (E2CO), fall short in long-term...

... network scaling method geology rock type machine learning upscaling pcu-dl module accuracy architecture physics-constrained upscaling permeability value reservoir characterization pore segmentation equation representation sub-volume size permeability prediction du-dl constraint...

... shows a field application of machine learning (ML) algorithms using triple combo logs to predict elastic properties and finally estimate in-situ stress profile in the Natural Buttes gas field. We used a complete set of triple combo and dipole sonic logs to train K-Nearest Neighbors (KNN) regression...

... deep learning social responsibility geologist artificial intelligence flow in porous media machine learning geological subdiscipline refinement efficiency journal placement sepehrnoori gradient sustainable development optimization realization international journal optimization...

... approach using machine learning to create a model for predicting the behavior of the cementation exponent "m" (it is a function of the shape and distribution of pores) in Mexican Naturally Fractured Reservoirs (NFRs), aiming to reduce uncertainty in reserves calculations and risks on decision-making...

... can be used for fast and reliable decision-making as well as reservoir management. sedimentary rock history matching geology reservoir simulation geologist optimization problem rock type machine learning society gpsnet producer information wang workflow conference reservoir...

... selection machine learning geological subdiscipline simulation interaction algorithm scenario drill bit cutter information axis pycolmap coefficient video captured reservoir geomechanics cloud vector geometry rotation axis enabling rapid bit design improvement orientation video...

..., it is time-consuming, inconvenient, and complicated. This work aims to enhance the prediction efficiency and accuracy of MMP between CO 2 and crude oil under reservoir conditions by improved and integrated machine-learning approaches. A novel method is proposed to improve the forecasting accuracy...

... machine learning and pattern recognition techniques to create an input-output mapping. The field of AI-based models can be broadly categorized into two major groups: (1) data-driven proxy models that are trained on the data obtained from physics-based simulation models or on the monitoring/historical...

...-loop em algorithm compute single-loop em algorithm flop conditional realization algorithm artificial intelligence machine learning covariance matrix gmm configuration realization traditional single-loop em algorithm gaussian component computational cost log-likelihood function reservoir...

... mining social media big data natural language petroleum play type operation cloud computing machine learning knowledge management efficiency decision-making platform automation safety application workflow technology sustainable development accessed 07 15 optimization integration...

... fracturing shale oil mudstone machine learning eur dataset energy economics proppant usage clastic rock directional drilling rock type oil shale artificial intelligence geological subdiscipline complex reservoir efficiency shale gas profitability cll well development reservoir...

..., set is settled caving volume, and V ann is annulus volume. geology geologist wellbore design artificial intelligence wellbore integrity machine learning geological subdiscipline reservoir geomechanics data-driven model drilling operation reservoir characterization drillstring packoff...

... deep learning machine learning artificial intelligence architecture transformer prediction dataset efficiency multi-scale learning segmentation mask semantic segmentation task smoke detection smoke mask segmentation conference flare smoke detection smoke region relu-based linear...

... at the wellbore wall only for most wellbore stability applications, we provide modifications to DL-ROM framework to handle 1D stress vectors at the wellbore wall. Step 3: We then perform a Machine Learning based study to develop proxy solutions for single-value outputs including induced maximum and minimum...

... sedimentology sedimentary rock deep learning artificial intelligence machine learning depositional environment synthetic seismogram application information noise correlation coefficient synthetic dataset realization inversion porosity and vclay reservoir geomechanics geological subdiscipline...