Summary Recent field experiments have demonstrated that distributed acoustic sensing (DAS) can be used to record strain in fiber optic cable at mHz frequencies. However, the effect of fiber optic cable construction on strain transfer has not been evaluated. The laboratory experiments presented here were designed to mimic fiber optic cable cemented into a borehole that intersects bedrock fractures. Hydraulic stress on the fracture is expected to stretch the cemented borehole which can be sensed by DAS. In the laboratory, we cemented five different fiber optic cable constructions into a pipe and then strained the pipe periodically using stepper motors.
Kavousi, Payam (West Virginia University) | Carr, Timothy (West Virginia University) | Wilson, Thomas (West Virginia University) | Amini, Shohreh (West Virginia University) | Wilson, Collin (Schlumberger) | Thomas, Mandy (Schlumberger) | MacPhail, Keith (Schlumberger) | Crandall, Dustin (National Energy Technology Laboratory, US Department of Energy) | Carney, BJ (Northeast Natural Energy LLC) | Costello, Ian (Northeast Natural Energy LLC) | Hewitt, Jay (Northeast Natural Energy LLC)
Distributed acoustic sensing (DAS) technology also known as distributed vibration sensing (DVS) uses optical fibers to measure the dynamic strain at all points along the fiber (Parker et al, 2014). The DAS senses the vibration in the local environment around the fiber and provides a measure of the relative strain of the optical fiber. This remote sensing technique has provided unparalleled acoustic sampling from the subsurface during hydraulic fracturing of the horizontal MIP-3H well drilled in Marcellus Shale near Morgantown, WV. We will show that the energy of the extracted phase of DAS data (hDVS) has a strong negative correlation with natural fracture intensity P32. The hydrofracking stages with lower P32 show a higher DAS phase energy and vice versa. In addition, we will evaluate the correlation between DAS phase energy, microseismic energy, and injection energy during the hydrofracking in MIP-3H. DAS phase energy is linearly correlated with injection energy. The calculated microseismic energies, which are less than 0.1% of the injection energies, do not show a significant correlation with either DAS phase energy or injection energy. The negative correlation between P32 and either DAS phase energy or injection energy suggests less vibration in zones that are more naturally fractured. Numerous observed fractures from wireline image logs are resistive (healed), and appear to significantly control the hydrofracking efficiency in MIP-3H.
Presentation Date: Tuesday, September 26, 2017
Start Time: 10:35 AM
Presentation Type: ORAL
A new distributed temperature sensing (DTS) interpretation method used in horizontal injection wells characterizes static facies and highlights independent features called thermofacies. This method allows for evaluating the intrinsic dynamic responses of reservoir layers using a time-lapse approach, taking into account the skin changes during the well's life and the possible activation of structural elements such as faults and fractures. Based on DTS temperature analysis acquired during a well's shut-in period, this interpretation method provides two major results: the thermal performance indicator (TPI) and the thermofacies. The TPI adds a dynamic component to the static image of a well provided by openhole logs, even taking into account structural elements and inflow performance evaluation. When DTS inflow contributions are available, some independent facies (thermofacies) can be defined, showing the dynamic behavior of a well in a standalone mode. The main advantage of this interpretation method is to provide a tool capable of driving field development to optimize the production while focusing on those log facies characterized by the dynamic injection performance; not only based on their static petrophysical evaluation.
Gage, J.R. (University of Wisconsin) | Noni, N. (Montana Tech, Department of Geological Engineering) | Turner, A. (Micron Optics Inc.) | MacLaughlin, M. (Montana Tech, Department of Geological Engineering) | Wang, H.F. (University of Wisconsin)