Abstract
Drill string vibrations are one of the most serious problems encountered while drilling as the bit and drill string interaction with formations under certain drilling conditions usually induces complex shocks and vibrations into the drill string components resulting in premature failure of the equipment and reduced drilling penetration rate. In severe cases where shocks and vibrations accumulated into drill string till exceeded its maximum yield or torsional strength, fatigue will occur and thereby increase the field development costs associated with replacing damaged components, fishing jobs, lost-in-hole situations, and sidetracks. Thus, real-time monitoring for downhole generated vibrations and accordingly adjusting drilling parameters including weight on bit, rotary speed, and circulation rate play a vital role in reducing the severity of these undesirable conditions. Vibration optimization must be done incorporation with the penetration rate, as a minimum economical penetration rate is required by the operator. In this study, three penetration rate and vibration level models were developed for axial, lateral, and stick-slip drilling modes using both MATLAB™ Software neural network and multiple regression analysis. It is found that the three models' results for vibration level and penetration rate; as compared with those recorded drilling data; showed an excellent match within an acceptable error of average correlation coefficient (R) over 0.95. The prediction of penetration rate and vibration level is thoroughly investigated in different axial, lateral, and stick-slip vibration drilling modes to be able to best select the optimum safe drilling zone. It is found that the axial vibration could be dampened by gradually increasing the weight on bit and increasing rotary speed while both the lateral and torsional vibrations are enhanced by increasing the rotary speed and decreasing the weight on bit.