Introduction

The successive crises in the petroleum industry, some of them ongoing, have forced a dramatic reduction in the workforce while we produce more hydrocarbons than ever. Even before those crises, we were facing challenges. The vast amount of continuously streamed data of all types can induce data and information overload. A large number of potentially useful processes we can apply to this data are just overlooked.  

The data complexity is now beyond the capability of any single individual and of most teams to process quickly, rigorously, and economically. Yet, the remaining engineers still waste up to 50% of their time struggling with data rather than using it. Although they still have creative tasks and human decisions to make, they are also engaged in repetitive tasks adding little value to what could be automatically performed by a computer.  

The KAPPA-Automate (K-A) project was born from this E&P-centric perfect storm in order to mitigate its effects. We believe that the recent advances in IT and software provided the means to consolidate, automate, and free engineers to add value to their working time.

K-A was developed within a Consortium involving KAPPA’s large operator clients to define and validate together the candidate workflows for automation in the context of Dynamic Data Analysis.