Method and system for rate of penetration optimization using artificial intelligence techniques

A method for automatic optimization of rate of penetration (ROP), the method comprising:

• obtaining, by a computer processor, a plurality of drilling surface parameters for a field of interest;
• identifying, by a computer processor, an undefined compressive strength (UCS) data for a targeted formation of interest based on well logs;
• calculating, by a computer processor, a mechanical specific energy (MSE) data based on the identified UCS data for the targeted formation of interest;
• filtering, by a computer processor, the calculated MSE data based on the identified UCS data with a range for the targeted formation of interest;
• training, by a computer processor, a machine learning model using the drilling surface parameters as inputs;
• outputting, by a computer processor, a plurality of weights for drilling parameters in a ROP equation derived by using the trained machine learning model for the field of interest, wherein the drilling surface parameters are used as inputs;
• determining, by a computer processor, a plurality of weights for drilling parameters in a Teale's MSE equation for the field of interest, wherein the drilling surface parameters are used as inputs;
• outputting, by a computer processor, a plurality of weights for drilling parameters in the Teale's MSE equation for the field of interest, wherein the drilling surface parameters are used as inputs;
• combining, by a computer processor, the machine learning ROP equation with the Teale's MSE equation to form a set of two equations;
• determining, by a computer processor, a plurality of optimum drilling parameters by simultaneously solving the set of machine learning ROP equation and the Teale's MSE equation;
• generating, by a computer processor, a work order to adjust the drilling parameters based on the determined optimum drilling parameters and previous drilling parameters;
• and
• causing, by a computer processor, display of the work order and the determined optimum drilling parameters in a user interface of a client device.