Lost circulation is a serious problem that imposes some extra costs to petroleum and gas exploration operations. Substantial technical and economic benefits can be accomplished if the severity and frequency of mud loss are considered during the well planning procedure. This will lead to preventing the occurrence of losses by using treatments/solutions that are applied before entering lost circulation zones. In the present work, new models were developed to predict the amount of lost circulation using artificial neural networks (ANNs). This model was implemented to obtain a deeper understanding of the relations between the losses rate and the controllable drilling variables (i.e., rate of penetration [ROP], flow rate [FR], circulation pressure [CP], weight on bit [WOB], and rotation per minute [RPM]). The losses rate was found to be sensitive to high ROP, FR, and CP, such that increasing these parameters continuously increase the amount of lost circulation. While a slight rise in the losses rate was observed at high WOB and RPM. The proposed ANNs model was used to predict the losses rate for two wells, and comparison plot (actual amount of lost circulation versus predicted) was introduced as a function of depth. An accurate and early prediction of lost circulation has been of great importance to avoid the risks associated with this problem's occurrence.

You can access this article if you purchase or spend a download.