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Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35042-MS
... reservoir characterization sedimentary rock drilling operation elkatatny artificial neural network well-b automating prediction accuracy formation 2 correlation coefficient geological subdiscipline prediction dataset rop mahmoud well-a offshore technology conference penetration...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35306-MS
... grouping data points based on their proximity in the dual-parameter domain. Then, a Convolutional Neural Networks (CNN) architecture is designed to synthesize the outcomes of the clustering analysis with the extensive dataset obtained from Cone Penetration Testing (CPT). This network undergoes a training...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35325-MS
... intelligence deep learning coefficient geological subdiscipline dla campeche dataset reservoir characterization prediction mra equation shear wave velocity determination seafloor structural geology cone resistance taboada phyllosilicate correlation machine learning database bay offshore...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35364-MS
... aims at integrating the reconstructed CPT logs, the UHR seismic images, and the horizon models into simultaneously estimating multiple geotechnical properties such as cone-tip resistance (RES) and friction ratio (FRR) via semi-supervised DL. As tested over the public Borssele dataset within the Dutch...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35355-MS
... data confirms. The application of this dataset allows users to assess how close to the limits of experience their developments are and to appropriately manage those risks, whilst noting that the pipe manufacturers may have qualified designs to more onerous criteria. To quantify the experience of use...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35354-MS
... described in this paper was to test the added value of the shear wave velocity (Vs) interpreted from the UMASW, particularly as a propagation tool of the geotechnical information. This requires a suitable Vs dataset within the foundation depth and the quantification of the associated uncertainties. The Vs...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35371-MS
... lno triantafyllou offshore technology conference dataset cylinder deep learning real time system algorithm neural operator firstling digimar lstm-modnet firstling-digimar forecasting Introduction Marine risers are vital components in offshore engineering as they serve as conduits...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35394-MS
... regression analysis on the steel catenary riser dataset, it is necessary to consider specific task requirements, data characteristics, and computational resources when building the graph neural network framework for each type of graph convolution layer. Graph Pooling Layers The graph pooling layer...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35276-MS
... Super Learner, and Multilayer Perceptron Neural Network (MLPNN)—for predicting bubble-point pressure as a function of the reservoir temperature, gas gravity, solution gas-oil ratio, and oil gravity (API). Utilizing a comprehensive dataset derived from different published papers, a total of 776 data...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35230-MS
... injection datasets. The efficacy of the WNO model was evaluated through CO 2 forecasts on the SACROC dataset, while the trained FNO model on the SACROC dataset was "transferred" to make predictions on the Sleipner dataset. The WNO-based ML method was accurate and efficient, such that the overall mean...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35265-MS
.... geologist spatial reasoning lateral variability dataset reservoir characterization application alternative approach structural geology artificial intelligence ground model figure 3 offshore technology conference algorithm mesh refinement reservoir simulation interpolation information...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35331-MS
... dataset hurricane logger stream jip scr event miv viv conservatism magnitude response mid-depth logger linear summation summation category offshore technology conference scr dataset Introduction SCRs are an extensively used riser systems in deep water oil and gas production...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35401-MS
... dataset artificial intelligence monitoring dataset subsurface information algorithm sparse machine learning workflow information time-lapse seismic data acquisition cost offshore technology conference geology reservoir characterization baseline dataset reconstruction geophysics efficiency...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35425-MS
... prediction cement formulation cement slurry dataset accuracy application offshore technology conference validation hydration thickening time algorithm cement thickening time operation Introduction Cementing is a crucial operation in the petroleum industry, used for zonal isolation, casing...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35456-MS
...: In this step, an analysis of the relationships between various CO 2 -EOR characteristics is conducted by the correlation analysis method. In step 1, 5,000 sets of models and simulation results have already been generated. Based on this dataset, eight machine learning models are trained and assessed to forecast...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35433-MS
... capabilities. This study investigates the use of machine learning (ML) techniques to forecast drilling fluid gel strength. A dataset comprising surface drilling parameters and laboratory gel strength measurements was gathered to construct ML models. Selected drilling parameters, such as mud weight and Marsh...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35439-MS
.... cloud computing requirement information interface artificial intelligence dataset stakeholder offshore technology conference facilitating digital delivery aid informed decision acquisition software subsea system interaction accessibility knowledge database infrastructure operator...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35500-MS
... consideration subsea system port exploration mineral exploration operation cook islands deployment expedition sustainability environmental impact assessment remotely operated vehicle offshore technology conference moana mineral dataset anuanua moana remote region personnel exploring otc-35500...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32304-MS
..., and their production throughput. One of the challenges is that the size of the dataset is less than 200 data points, largely due to the limited total number of FPSOs worldwide. Another challenge is that there are missing values for gas production, as such, imputation of missing values becomes necessary. In this study...

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