Comparison between Bit Optimization Using Artificial Neural Network and Other Methods Base on Log Analysis Applied in Shadegan Oil Field

Abstract

Abstract Bit selection is one of the main challenges in drilling operations. Since the effect of drilling bit in total cost is inevitable, bit selection is introduced as a vital task in planning and designing new wells. Using bits with proper code improve bit drillability otherwise false code leads in readily damage and wear the bit. Bit selection is based on the history performance of similar bits from offset wells and also is done by different methods based on offset well logs. There are many parameters intervening in drilling bit selection. Therefore, developing a logical relationship among them to assist in proper bit selection is necessary and complicated though. In such a case, Artificial Neural Networks (ANNs) is proven to be helpful in recognizing complex connection between variables. Well logs expose different parameters of the formation; one of the most important parameter is hardness of the formation which can help us choosing proper bit. So we can have a comparison between two methods and check the answers with history drilling data of field.