MACHINE LEARNING ASSISTED PARAMETER MATCHING AND PRODUCTION FORECASTING FOR NEW WELLS

Systems and methods for machine learning (ML) assisted parameter matching are disclosed. Wellsite data is acquired for one or more existing production wells in a hydrocarbon producing field. The wellsite data is transformed into one or more model data sets for predictive modeling. A first ML model i...

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Hauptverfasser: Bansal, Yogesh, Mijares, Gerardo
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creator Bansal, Yogesh
Mijares, Gerardo
description Systems and methods for machine learning (ML) assisted parameter matching are disclosed. Wellsite data is acquired for one or more existing production wells in a hydrocarbon producing field. The wellsite data is transformed into one or more model data sets for predictive modeling. A first ML model is trained to predict well logs for the existing production well(s), based on the model data set(s). A first well model is generated to estimate production of the existing production well(s) based on the predicted well logs. Parameters of the first well model are tuned based on a comparison between the estimated and an actual production of the existing production well(s). A second ML model is trained to predict parameters of a second well model for a new production well, based on the tuned parameters of the first well model. The new well's production is forecasted using the second ML model.
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subjects EARTH DRILLING
EARTH DRILLING, e.g. DEEP DRILLING
FIXED CONSTRUCTIONS
MINING
OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS
title MACHINE LEARNING ASSISTED PARAMETER MATCHING AND PRODUCTION FORECASTING FOR NEW WELLS
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