Machine-learning for sedimentary facies prediction
Using machine learning for sedimentary facies prediction by using one or more logs acquired in a borehole. This includes performing a petrophysical clustering of borehole depths wherein the depths of the borehole are gathered into clusters based on similarities in the one or more logs. Also performe...
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| creator | Boyd, Austin Bize-Forest, Nadege Lima de Carvalho, Lucas Lima Angelo dos Santos, Laura Baines, Victoria Kherroubi, Josselin Schlicht, Peter |
| description | Using machine learning for sedimentary facies prediction by using one or more logs acquired in a borehole. This includes performing a petrophysical clustering of borehole depths wherein the depths of the borehole are gathered into clusters based on similarities in the one or more logs. Also performed is a log inclusion optimization, including a selection of one or more parameters of the petrophysical clustering, wherein the one or more parameters include a number and/or type of considered logs among the one or more logs and/or a clustering method. Also performed is a classification of the clusters into core depositional facies using one or more predetermined rules. |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES DETECTING MASSES OR OBJECTS EARTH DRILLING EARTH DRILLING, e.g. DEEP DRILLING ELECTRIC DIGITAL DATA PROCESSING FIXED CONSTRUCTIONS GEOPHYSICS GRAVITATIONAL MEASUREMENTS MEASURING MINING OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TESTING |
| title | Machine-learning for sedimentary facies prediction |
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