Abstract

This paper discusses a university research project assisted by the SPE Mentoring Program. The purpose of the research is to provide a thorough examination of the formation behavior of the lateral target simultaneously while the well is being drilled in real time; this is to help engineers better characterize the formation appropriately and ultimately enable a detailed customization of the completion plan to optimize performance. It is of significance that this examination is already being used for drilling optimization and is performed using commonly available data. This investigation provides a benefit at no additional expense for the operator to perform.

For this study, real-time drilling data metrics are recorded from existing wells and observed to compare against the position of the wellbore in the targeted geology. These parameters are used to examine formation behavior as well as produce a functional mechanical specific energy (MSE) output to enable further investigation and correlation. The completions report is also inspected to confirm correlations against problem stages. Success or failure of the stages confirms correlation. Finally, a proposal is given to enhance and individualize a completions design for the drilled well.

This study used drilling and completion data from several Bakken wells. The relationship of drilling energy (MSE) to hydraulic stimulation energy parameters is shown. An MSE index is made and a suggested completion stage design is given based on the index. With the gathered data, the completions team has sufficient information, suggesting precise completion parameters to ultimately eliminate stage failures and improve overall execution. These suggestions become available for the completions team to use the moment that the drilling process is concluded.

It is imperative that the existing data metrics are used to improve and enhance completions performance. Quality screening is necessary because of the complexity, volume, and detail of the data metrics. The data being used behaves dynamically for varying regions, formations, and equipment. The ultimate goal is to harness the existing information and better understand how the formations are behaving during the drilling process, allowing for exploitation with respect to the completions process.

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