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Stimulated Fractured Reservoir DFN Models Calibrated With Microseismic Source Mechanisms
| Content Provider | Semantic Scholar |
|---|---|
| Author | Williams-Stroud, Sherilyn Eisner, Leo |
| Copyright Year | 2010 |
| Abstract | Methods for constraining discrete fracture network (DFN) models have historically relied on two very different scales for data: large-scale sources from which attributes can be coarsely defined for volume elements of 1000s of cubic meters such as seismic data, or small-scale sources where attributes of individual fractures are measured on a meter scale such as wellbores. Populating reservoir models with wellbore data requires upscaling the measured parameters, and the use of the large scale data types is accompanied by assumptions that can have significant uncertainties. A source of data that fills the gap intermediate to the large and small scale fracture parameters is microseismic data. During reservoir stimulation or production, acquisition of microseismic data with a surface array of geophones laid out in multiple azimuths and offsets (e.g., a star-like pattern above the well, or shallowly buried geophones in a grid like pattern), provides a broad sampling of the focal sphere that can be used to invert microseismic events for the source mechanism. This paper presents examples of DFN models constrained with source mechanisms and the implications for reservoir modeling of these more-highly constrained fracture network models. for reservoir simulation [1, 2] Fracture models used for reservoir characterization are often constructed by inferring a bulk fracture intensity based on seismic attributes such as seismic coherency or anisotropy, and a general orientation of fractures for relatively large volume elements can be defined using seismic velocity anisotropy [3, 4]. DFN models are also constrained by fracture data from wells, but this only provides information about the fracture character in a small portion of the reservoir [5, 6], and workers have developed various methods to extrapolate wellbore data to the reservoir scale [7, 8]. The use of well data and seismic attributes in the same reservoir model requires some method to upscale the well data to the bulk property scale data derived from the seismic attributes. Often the well scale is so small relative to the reservoir volume element that the correlation between fracture frequency measured along a well bore and a fracture intensity property derived from seismic data is extremely coarse and the resolution is insufficient for the type of well spacing decisions needed for development of unconventional reservoirs. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.microseismic.com/wp-content/uploads/2017/07/2011-ARMA_Stimulated_Fractured_Reservoir_DFN.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
