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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 6–8, 2024
Paper Number: SPE-217803-MS
...) , applied machine learning models and advanced multivariate regression techniques, in efforts to assess the relative importance of various parameters affecting well productivity. Cross plotting 6-month normalized well-level production against a few of these variables in the DJ basin helps illustrate...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 6–8, 2024
Paper Number: SPE-217777-MS
..., machine learning (ML) systems, overseen by human analysts, monitored and identified FDIs in real-time and relayed them to the team managing the operation. This operation is the first instance where disposable fiber, or any fiber, was used explicitly for managing simultaneous subsurface operations...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 6–8, 2024
Paper Number: SPE-217781-MS
... learning model will probably be required in order to generalize and scale the workflow up. Using a combination of a rule-based algorithm and machine-learning model, identify the end of pumping events and parse out water hammer signature and pressure decline at the end of a frac stage ( Figure 2...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209171-MS
... machine learning data quality hydraulic fracturing production control unconventional resource economics basin child well change boxplot upstream oil & gas completion date difference well pair distribution parent well artificial intelligence directional drilling drilling operation parent...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209141-MS
... completion installation and operations upstream oil & gas erosion rate fracturing materials proppant test series 1 erosion petroleum engineer test series 2 hole size tank perforation machine learning proppant placement hydraulic fracturing mesh sand friction reducer perforation erosion...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209161-MS
... with mapping real-time data have been made. The application of machine learning techniques, particularly signal processing filters, down-sampling, and creating binary-valued logic on a real-time scale has previously demonstrated the ability to accurately define the start/end of a stage from the treatment data...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209134-MS
... by pumping a small volume of fracturing fluid over a small-time interval to evaluate and calibrate the formation properties to a design simulator. The sequence of steps from a machine learning framework are outlined below. Abstract Fracturing utilizes significant heuristics and biases...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209165-MS
... Abstract In unconventional wells, returns are driven in part by the reduction of variability in efficiency and performance. In 2021 the stimulation of two wells in the Bakken proceeded under the architecture of an automated frac control system communicating directly to Machine Learning...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, May 4–6, 2021
Paper Number: SPE-204199-MS
... Reservoir Characteristics. Abstract The subject of this paper is the application of a unique machine learning approach to the evaluation of Wolfcamp B completions. A database consisting of Reservoir, Completion, Frac and Production information from 301 Multi-Fractured Horizontal Wolfcamp B...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, May 4–6, 2021
Paper Number: SPE-204164-MS
... data quality reservoir geomechanics machine learning artificial intelligence reservoir characterization hydraulic fracturing natural fracture g-function analysis upstream oil & gas heat exchange soliman correction fracture closure pressure dfit geothermal reservoir drillstem...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, May 4–6, 2021
Paper Number: SPE-204193-MS
... pressure transient analysis reservoir characterization hydraulic fracturing fracturing fluid machine learning completion installation and operations complex reservoir drillstem/well testing frac stage pressure response completion monitoring systems/intelligent wells artificial...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, May 4–6, 2021
Paper Number: SPE-204153-MS
... to hydraulic fracturing. Figure 7 Apparent Viscosity vs. Shear Rate - Guar vs HVFR machine learning energy economics fracturing materials artificial intelligence proppant upstream oil & gas shale gas fracturing fluid chemical additive clay control reduction fracture treatment...
Proceedings Papers

Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, May 4–6, 2021
Paper Number: SPE-204139-MS
... by adjusting completion design in these areas. chemical tracer data mining complex reservoir perforated interval machine learning artificial intelligence tracer test analysis curvature correlation tracer recovery identify performance driver reservoir characterization completion installation...

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