Semester

Fall

Date of Graduation

2021

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Petroleum and Natural Gas Engineering

Committee Chair

Ebrahim Fathi

Committee Member

Ebrahim Fathi

Committee Member

Ming Gu

Committee Member

Samuel Ameri

Abstract

Interstage communication during well stimulation reducing the effectivity of the well completion is known to be a concern in the oil and gas industry. The leading cause of this is fracture communication due to the presence of natural fractures where the formation is being hydraulically fractured. In this study, a technique was developed to map natural fractures, on a larger scale, underground to be able to avoid the high fracture intensity zones when hydraulically fracturing. This study developed a technique to optimize well completion designs by introducing the ability of locating natural fractures zones in the formation (Marcellus Shale) which leads to better cluster efficiency, the minimization of clusters merging, and the absence of fracture communication.

The MSEEL well pads, MIP and Boggess, were equipped with fiber optic cables that provides data such as DAS (Distributed Acoustic Sensing), DTS (Distributed Temperature Sensing), and Slow Strain data. Additional data were generated such as the formation geomechanical properties (brittleness and fracability) as well as the completion reports (injection pressure, fluids concentrations). Basically, the approach used in this study was to integrate the completion designs of the boggess pad wells with the generated resistivity image logs, to identify the fracture intensity. Furthermore, the fiber optic DAS data was used to determine the cluster efficiency for each stage, while the fiber optic slow strain was mapped to identify the locations and times of the fracture hits from the treatment well (Boggess 5H) onto the monitoring well (Boggess 1H).

At first, the fracture intensity was plotted with respect to depth in order to locate the high fracture intensity zones in the formation. Secondly, the fiber optic slow strain was used to determine the time and depth of the frac hits. Following that was the generation of the cluster efficiency log to identify, on each stage, the clusters with the highest and lowest energy. Knowing that boggess 5H and 1H are spaced by 1500ft, it was found that the depth of the frac hit on the treatment well 5H was different from where the monitoring well detected the same frac hit. In stage 13 for instance, well 5H shows a frac hit at a depth of 16,762ft while the well 1H shows the hit at a depth of 16,820ft, showing that this was not a 1:1 correlation. It was also observed that the clusters with the lowest energy received were located in high fracture intensity zones and vice versa.

This study developed a data derivative technique that allows for the localization of natural fractures, which can lead the engineers to avoid perforations in the high fracture intensity zones. The older techniques for mapping would only locate natural fractures around the wellbore, while this technique incorporates mapping on a larger (pad) scale. Actual data such as fracture intensity and slow strain were used in this study for the natural fracture mapping rather than hypotheses and statistical analyses used by the older techniques. Seeing that this process worked on the example case shown in this report, the technique will be applied on the remaining scenarios (9H-5H, 9H-1H). Thus, this newly developed technique optimizes the completion design and helps avoid any detrimental impacts such as frac hits on nearby wells.

Embargo Reason

Publication Pending

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