Methods for generating synthetic production logs for perforated intervals of a plurality of wells

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the computing device to:

• access historical data from a plurality of databases, the historical data including well production data of a plurality of wells, well completions data, flow meters data, and well rate tests data;
• access historical perforation data and historical reservoir properties data from a simulation model;
• train, using a plurality of input values, a machine learning model for predicting oil flow values at the perforated intervals of a plurality of target wells, wherein the plurality of input values comprise fluid flow values and rock quality index values associated with perforated intervals of the plurality of wells that are based at least in part on the historical perforation data and the historical reservoir properties data from the simulation model, and wherein the fluid flow values and rock quality values are linked to the well production data included in the historical data of the plurality of wells;
• predict, using the trained machine learning model, the oil flow values at the perforated intervals of the plurality of target wells;
• and
• generate a synthetic production log that includes the oil flow values at the perforated intervals of the plurality of target wells.

A method implemented by one or more computing devices, the method comprising:

• accessing historical data from a plurality of databases, the historical data including well production data of a plurality of wells, well completions data, flow meters data, and well rate tests data;
• accessing historical perforation data and historical reservoir properties data from a simulation model;
• training, using a plurality of input values, a machine learning model for predicting oil flow values at the perforated intervals of a plurality of target wells, wherein the plurality of input values comprise fluid flow values and rock quality index values associated with perforated intervals of the plurality of wells that are based at least in part on the historical perforation data and the historical reservoir properties data from the simulation model, and wherein the fluid flow values and rock quality values are linked to the well production data included in the historical data of the plurality of wells;
• and
• predicting, using the trained machine learning model, the oil flow values at the perforated intervals of the plurality of target wells.