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Abstract Over the past decade, microseismic monitoring has become the approach most often used to gain an in-situ understanding of the rock's response during hydraulic fracture stimulations. Recently, the utilization of distributed geophone arrays around treatments has provided for an opportunity to investigate the way these fractures develop by examining the microseismic events recorded during a stimulation. Thru microseismic (MS) monitoring currently being carried out in the Horn River formation, geophysicists and reservoir engineers incorporated MS field data and its original interpretation to constrain and validate reservoir models. Generally, we have observed that overall fracture height, width and length, orientation, and growth vary from formation to formation and within each formation. In the presence of uncertainty in reservoir models input data required for determining the best estimate of a value, probabilistic methods are used. Risk analysis is a technique to quantify the impact of uncertainties on output variables, and to determine a range of possible outcomes, as opposed to a single deterministic solution. The uncertainty in the output also provides a measure of the validity of a reservoir model. In this paper we use Monte Carlo simulation using Latin Hypercube sampling by using probability density functions (PDFs) and cumulative distribution functions (CDFs) that describe the likely values of MS fracture half-length and MS fracture height as input parameters into the reservoir model. PDFs and CDFs can be established and used to provide more realistic estimates of stimulation parameters such as Stimulated Reservoir Volume (SRV) which are calibrated with MS SRVs Microseismic Interpretation of events provides an upper bound value for stage fracture half-length and fracture height in unconventional shale gas reservoirs. The cumulative distribution function of stage fracture half-length and fracture height on a well basis on a multi-fractured horizontal well pad provides insight on the understanding of what the ultimate stage by stage SRV could be after pressure depletion occurs and what are the implications for well spacing and well placement in multiwell pad design. This allows a probabilistic approach to production forecasting and reserves estimation and to calculate a robust P10 estimate of Expected Ultimate Recovery and Recovery Factor. This approach differs from previous work that is based on strong collaborative work between geophysicists and reservoir engineers. This paper will show a more recent multi-well pad and, microseismic interpretation, and contribute technically to the knowledge of the unconventional shale oil and gas industry through the Integration of two multidisciplinary disciplines such as Geophysics and Engineering, constrain of Analytical Models which can be used as quick look first pass into numerical simulation deck files, and estimation of production forecasting and different reserves categories including Proved Developed Producing (PDP), Proved + Probable Developed Producing (PPDP) and Undeveloped (PUD & PPUD). Furthermore, some of the design considerations of the newly completed multi-well pad, surveillance data such as production logs, chemical fluid and radioactive tracers and production indications will be addressed and considered, concluding with a discussion of the results.
Summary Over the past decade, microseismic (MS) monitoring has become the primary approach used to gain an in-situ understanding of the rock's response during stimulation. Recently, the utilization of downhole monitoring of treatments has provided an opportunity to investigate ways by which these fractures develop by examining microseismic events recorded during stimulation. In the Horn River, geophysicists and engineers used microseismic field data and its interpretation to constrain reservoir models. Generally, it has been observed that fracture height, width and length vary from formation to formation. In the presence of uncertainty in reservoir models, input data is required for determining the best estimate of a value, and probabilistic methods are used. Risk analysis is a technique used to quantify the impact of uncertainties on output variables, and to determine a range of possible outcomes. In this paper we use Monte Carlo simulation and probability density functions (PDFs) that describe likely values of fracture half-height as an input parameter into reservoir models. PDFs and Cumulative Distribution Functions (CDFs) are used to provide realistic estimates of stimulation parameters, such as stimulated reservoir volume. Microseismic interpretation of events provides an upper bound value for fracture half-height in unconventional shale gas reservoirs. Its CDF for each well on a multi-fractured horizontal well pad provides a better understanding of what the ultimate fracture half-height could be after pressure depletion, and what the resulting implications for well spacing/ placement in pad design are. This facilitates a probabilistic approach to production forecasting and reserves estimation, and allows us to calculate a robust estimate range of estimated ultimate recovery (EUR) and recovery factor (RF). This approach differs from previous work that is based on strong collaborative work between geophysicists and engineers. This paper contributes technically to the knowledge of the unconventional shale oil and gas industry by constraining analytical models that can be used as a quick look/ first pass into numerical simulation, and as estimators of production forecasts and different reserves categories. Furthermore, some of the design considerations of the multi-well pad, in addition to surveillance data – such as production logs, chemical fluid and radioactive tracer – will be addressed, concluding with a discussion of the results.
Abstract A vast number of the reported cases of increased seismicity of moderate magnitude (Mw > 0) earthquakes seem to be tied to some form of fluid injection activitiy, being it wastewater disposal by injection into deep wells or high pressure fluid injection into oil and gas reservoirs to hydraulically fracture the rock and improve hydrocarbon recovery. Regulations have been proposed to implement traffic light systems to dictate the responses that the industry needs to take based on either the magnitudes or observed particle velocities or accelerations on the surface. In order to relate the seismic hazard potential in seismically active areas, empirical ground motion prediction equations (EGMPE) are used to relate event parameters like magnitude and location to site characteristics such as peak ground acceleration (PGA) or peak ground velocity (PGV) which tend to be how building codes are parametrized. Therefore, local hazard assessment near hydraulic fractures that generate relatively large magnitude events need to be estimated more precisely by developing and using local EGMPEs. Hybrid deployments combining 15Hz downhole and low frequency near-surface geophones can be used to accurately capture both the localized microseismic events and any large magnitude events associated with hydraulic fracture monitoring across North American basins – Horn River, Eagle Ford, Barnett, and Montney for example. In our studies events with M>0 are observed for completions in these formations. While in many cases the magnitude of these events is too small to be felt on the surface, there are reports of higher magnitude events which have been sensed by workers on site and the local population. The exact relationships between magnitudes and shaking are not necessarily one-to-one. Shaking also varies based on the stress release of the events. As summarized recently by Hough (2014) for other fluid-induced seismicity, the lower stress releases typical for these sequences results in on-average less shaking than is observed for equivalent magnitude tectonic events. In order to quantify shaking over a seismogenic volume, we show how to develop EGMPEs based on the North-American examples. The EGMPE methodology developed in this study can be extrapolated for similar earthquakes of larger magnitude and included into future probabilistic hazard and risk analysis for induced seismicity as related to hydraulic fracture stimulations.