Horizontal receiver azimuth orientation estimates and poststack inversion

Abstract

The oil and gas industry is inherently volatile, and as a result, industry downturns force companies to become more efficient. Companies that adapt and successfully control operating costs, while maximizing reserves, survive these downturns relatively unscathed. Unconventional reservoir plays can be prolific hydrocarbon producers, but require hydraulic fracturing to enhance production. These reservoirs are generally complex, heterogeneous, and reservoir characterization becomes extremely difficult, yet is critical for success. Utilizing time-lapse (4-D), nine-component (9-C) seismic data to characterize these reservoirs can aid recovery. My 4-D, 9-C datasets are from the Wattenberg Field, Colorado, USA, and the reservoir targets are chalk formations within the Niobrara Formation and the Codell member of the Carlile Formation. I performed a post stack sparse-layer inversion that appears to resolve the chalk benches within the Niobrara Formation. These results are compared to published regional sequence stratigraphic framework. In addition, this inversion was performed in a time-lapse sense to monitor how the reservoir has changed after two years of production. These time lapse results correlate well with microseismic events and modeled hydraulic fracture conductivity. There is an overall increase in time lapse-change in the North-Western portion of the section that correlates with higher production. Analysis and interpretations of seismic data are critical to successful reservoir characterization, but when there are dataset issues (pertaining to acquisition and/or processing) this leads to incorrect interpretations. In addition to the post stack inversion, I expose errors in the H1 orientation for the Monitor 1 survey (acquired immediately post-hydraulic fracturing) that are consistent enough to produce coherent converted-wave (C-wave), and shear-wave (S-wave), reflection signal on the crossterms after rotation to radial-transverse coordinates. I then utilize two scanning methods to estimate the H1 azimuth orientation for each receiver gather. All three surveys were then re-rotated into radial-transverse coordinates with the appropriate H1 orientation azimuths.