Abstract:
A workflow using techniques for improving signal-to-noise ratio and decreasing interferences for Low-Frequency Distributed Acoustic Sensing is described.
Abstract:
A method of assessing cross-well interference and/or optimizing hydrocarbon production from a reservoir by obtaining low frequency DAS and DTS data and pressure data from a monitor well, when both the monitor and production well are shut-in, and then variably opening the production well for production, and detecting the temperature and pressure fluctuations that indication cross-well interference, and localizing the interference along the well length based on the low frequency DAS data. This information can be used to optimize well placement, completion plans, fracturing plans, and ultimately optimize production from a given reservoir
Abstract:
A method of monitoring hydraulic fracturing using DAS sensors in a treatment well and/or observation well is described. The raw data is transformed using a low pass filter (≦0.05 Hz) and down-sampled to show the signal as the stimulation progresses. The resulting data can be used to optimize the hydraulic fracturing or improve reservoir models for other reservoirs.
Abstract:
Methods and processing in the field of seismic data, particularly to more accurately predict petrophysical property variables at unsampled locations beyond and between wells.
Abstract:
A data acquisition program, which includes core, image log, microseismic, DAS, DTS, and pressure data, is described. This program can be used in conjunction with a variety of techniques to accurately monitor and conduct well stimulation.
Abstract:
Monitoring and diagnosing completion during hydraulic fracturing operations provides insights into the fracture geometry, inter-well frac hits and connectivity. Conventional monitoring methods (microseismic, borehole gauges, tracers, etc.) can provide a range of information about the stimulated rock volume but may often be limited in detail or clouded by uncertainty. Utilization of DAS as a fracture monitoring tool is growing, however most of the applications have been limited to acoustic frequency bands of the DAS recorded signal. In this paper, we demonstrate some examples of using the low-frequency band of Distributed Acoustic Sensing (DAS) signal to constrain hydraulic fracture geometry. DAS data were acquired in both offset horizontal and vertical monitor wells. In horizontal wells, DAS data records formation strain perturbation due to fracture propagation. Events like fracture opening and closing, stress shadow creation and relaxation, ball seat and plug isolation can be clearly identified. In vertical wells, DAS response agrees well with co-located pressure and temperature gauges, and illuminates the vertical extent of hydraulic fractures. DAS data in the low-frequency band is a powerful attribute to monitor small strain and temperature perturbation in or near the monitor wells. With different fibered monitor well design, the far-field fracture length, height, width, and density can be accurately measured using cross-well DAS observations.
Abstract:
Tools and methods for monitoring a subterranean formation is provided. Methods for monitoring include: creating a time-lapse azimuth stack between an azimuth stack on a first seismic survey and an azimuth stack on a second seismic survey; identifying a lowest root mean square energy and a highest root mean square energy for each time-lapse azimuth stack; and recording an azimuth with largest overall root mean square energy.
Abstract:
Methods and systems for assessing cross-well interference and/or optimizing hydrocarbon production from a reservoir by obtaining low frequency DAS and DTS data and pressure data from a monitor well, when both the monitor and production well are shut-in, and then variably opening the production well for production, and detecting the temperature and pressure fluctuations that indication cross-well interference, and localizing the interference along the well length based on the low frequency DAS data. This information can be used to optimize well placement, completion plans, fracturing plans, and ultimately optimize production from a given reservoir.
Abstract:
A method of optimizing production of a hydrocarbon-containing reservoir by measuring low-frequency Distributed Acoustic Sensing (LFDAS) data in the well during a time period of constant flow and during a time period of no flow and during a time period of perturbation of flow and simultaneously measuring Distributed Temperature Sensing (DTS) data from the well during a time period of constant flow and during a time period of no flow and during a time period of perturbation of flow. An initial model of reservoir flow is provided using the LFDAS and DTS data; the LFDAS and DTS data inverted using Markov chain Monte Carlo method to provide an optimized reservoir model, and that optimized profile utilized to manage hydrocarbon production from the well and other asset wells.
Abstract:
A method of optimizing production of a hydrocarbon-containing reservoir by measuring low-frequency Distributed Acoustic Sensing (LFDAS) data in said well during a time period of constant flow and during a time period of no flow and during a time period of perturbation of flow and simultaneously measuring Distributed Temperature Sensing (DTS) data from said well during a time period of constant flow and during a time period of no flow and during a time period of perturbation of flow. An initial model of reservoir flow is provided using the LFDAS and DTS data; the LFDAS and DTS data inverted using Markov chain Monte Carlo method to provide an optimized reservoir model, and that optimized profile utilized to manage hydrocarbon production from said well and other asset wells.