Summary Tight gas, low-permeability reservoirs offer a tremendous challenge with respect to effectively completing and draining a target reservoir. Openhole-packer completions in horizontal wells offer a cost-efficient means of accessing the entire lateral section, assuming the target pay can be effectively stimulated. The challenge with openhole completions compared with more-conventional cased, cemented, and limited-entry perforated completions is understanding and controlling hydraulic-fracture geometry—specifically, the number and location of fracture-initiation points and the fracturing-fluid flow into the near-wellbore (NWB) region of the reservoir. Fiber-optic-based distributed temperature sensing (DTS) offers a method for identifying, quantifying, and evaluating the NWB fracture geometry, the fracturing-fluid distribution in these broad openhole sections, and overall stimulation effectiveness. DTS can also reveal success or issues with respect to effective zonal isolation when using mechanical isolation during the hydraulic-fracturing process. In this particular case study, a lateral well in a basin-centered gas area was completed with swell-packer interval isolation by use of fracture sleeves for reservoir access. By coupling fracture-treatment responses and openhole log characteristics with the NWB DTS data during pumping and warm back, an integrated assessment of the completion stimulation effectiveness and efficiency was performed. The end result of this assessment provided an improved understanding of the current completion performance and allowed optimization of openhole completion projects for future wells in this same area.
Mapping the microseismic activity during a hydraulic treatment is widely used to determine the geometry of the stimulated fracture network. Microseismic maps provide reliable information on the development of fracture symmetry, half-length, azimuth, width and height, and their dependence on the treatment parameters and reservoir characteristics. Beyond that, these fracture geometries are used to better understand fracture modeling and even production characteristics. Fiber-optic-based distributed temperature sensing (DTS) arrays provide almost immediate updates of the near-wellbore temperature distribution in approximately one-meter intervals. In injection treatments, the near-wellbore temperature distribution can be used to determine isolation effectiveness, the relative amount of fluid each perforation cluster takes, fracture initiation points, and effective fluid diversion. In production analysis, DTS measurements can quantify production rates from each perforation interval, crossflow rates while shut-in, and fluid types recovered from each perforation interval. The detailed near-wellbore results available through DTS coupled with the far-field geometry acquired through microseismic mapping provide an accurate picture of the completion effectiveness. Microseismic mapping results often show adequate resolution over a large area but lack the fine resolution that would allow it to identify near-wellbore effects in the meter range. When modeling and interpreting the treatment geometry obtained by the microseismic-event distribution, it is important to include the correct near-wellbore effects, which are readily accessible through DTS measurements. Combining the two diagnostic tools is valuable for real-time decision making, post-treatment analysis, and production analysis to assess the completion effectiveness. Incorrect assumptions about perforation breakdown, fracture-initiation points, interval isolation, or limited-entry effectiveness can lead to misinterpretations of the microseismic results. Using both diagnostic tools provides firm answers to the overall completion effectiveness. This paper focuses on three distinct aspects of combining the analysis of microseismic mapping and DTS. The first is the real-time aspect, wherein real-time decisions and adjustments are made during the fracture treatment with the objective of manipulating the results towards the desired outcome. The second is using both tools to perform more accurate postfracture analysis, including calibrated fracture modeling, entry effectiveness, correct interval spacing, and stimulated reservoir volume (SRV) analysis. The third area covered is combining these diagnostic tools with a production analysis, which is acquired through analysis of the temperature data.
Wellbore monitoring techniques are proving to be significant in reservoir management and intervention design, particularly in unconventional fields where fluid flow behavior is not very well understood. Distributed temperature sensing (DTS) technology allows for an estimation of zonal flow rates in the entire well as a function of time during hydraulic fracturing, as well as during the production phase.In this work, a novel transient thermo-hydraulic model that includes fluid transport and thermal coupling and simulates fluid flow and temperature in both the wellbore and reservoir is presented. Real DTS data from a hydraulic fracturing operation in a low-permeability basin in west Texas has been inverted using this model. Flow allocation based on the thermohydraulic model is presented. It was found that the reservoir heterogeneity, and hence the zonal flow rates, can be accurately obtained based on temperature and pressure data from the well.Most of the steady-state DTS data inversion models are typically applicable to production scenarios, where the transient in temperature has vanished. Injection operations, such as in fracturing where the temperature does not achieve a steady-state during the injection stage, require a transient model that can capture the initial-time effects. Also, some of these models fail to include the Joule-Thomson effect, and this leads to an incorrect flow allocation. The thermo-hydraulic model developed in this work includes both the Joule-Thomson and transient effects. It can be applied to non-reactive fluid injection during stimulation operations, such as matrix acidizing and fracturing. In particular, application of the model for fluid distribution before, during, and post-fracturing provides an estimate of the efficiency of fracturing stages.
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