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In this paper we demonstrate the use of the capillary pressure equilibrium theory (CPET) model to address the effects of partial saturation in order to estimate hydrocarbon saturation in a reservoir volume using acoustic impedances derived by seismic inversion. The data set used here has been donated by BHP Billiton, and is from an offshore oilfield called the Stybarrow field. The set comprises of a well with a 20-foot sandstone oil saturated pay section and 3D pre- and post-stack seismic volumes. Using the provided angle stacks and well log data, a statistical wavelet, and low impedance model, the final impedance model is computed. There are two final impedance models, derived from post-stack, and pre-stack data. The final impedance models are in agreement with one another at each of the well locations, with low impedance at the oil saturated well, and high impedance at the water saturated well. The corresponding CPET model is built based on the empirical porosity from the well log. The rock and fluid properties are available from the logs and petro physical reports provided by BHP Billiton. The CPET model has difficulty distinguishing between 0 and 30% water saturation. The impedances predicted by the CPET model are in good agreement at the two well locations (blind wells), predicting 98% oil saturation in the 97% oil saturated section, and 8% water saturation in the 5% water saturated section of the reservoir. Finally using the CPET workflow, a 3D distribution of saturation was computed from inversion derived acoustic impedance and the CPET model estimated from well log. Unlike conventional approaches of estimating saturation, our method is able to discriminate between patchy and uniform saturation. Our results on Stybarrow field data reveal that the Stybarrow field behaves in a manner very close to the uniform curve at low water saturation. However, starting at 30% water saturation or higher the distribution becomes slightly patchy.
Presentation Date: Wednesday, October 19, 2016
Start Time: 3:35:00 PM
Presentation Type: ORAL
We present a new method and a field data example for creating reservoir models that simultaneously match seismic and geologic data. Our method combines geostatistical simulation and multi-objective optimization, and it is used to improve static reservoir model estimation by simultaneously integrating multiple datasets including well logs, geologic information and various seismic attributes. The main advantage of our approach is that we can define multiple objective functions for a variety of data types and constraints, and simultaneously minimize the data misfits. Using our optimization method, the resulting models converge towards Pareto fronts, which represent the sets of best compromise model solutions for the defined objectives. We test our new method on a producing reservoir offshore Western Australia. The results of our study indicate that improved reservoir models can be obtained using our method, compared to current geostatistical modeling methods.
The advanced seismic technologies available today require timely planning and close integration to maximize their value. This requirement has been a red thread in all my previous feature reviews, and this is likely to continue. In this context, the feature reviews are an excellent means to increase technology awareness across disciplinary boundaries.
Broadband seismic is the watchword for the marine-seismic industry at present. Most major marine-seismic vendors have reacted quickly to this trend and introduced proprietary broadband solutions over the last 2 years. The advertised examples and case studies show remarkable improvements in vertical resolution, and broadband acquisition sooner or later will become the norm for most marine-seismic surveys. Especially the resulting extension of the low-frequency end of the signal spectrum has the potential to enhance reservoir characterization significantly, leading to a more reliable subsurface definition, and to facilitate full-waveform inversion, even in the absence of direct well control.
These are undoubtedly exciting developments, though the challenge remains to achieve similar breakthroughs in deeper, more geologically complex settings and also for onshore seismic. Broadband acquisition alone is not a panacea, and dense spatial sampling and rich azimuth acquisition for optimal subsurface illumination and imaging remain equally, if not more, important. Fortunately, broadband acquisition and wide-azimuth seismic are not mutually exclusive, and further improvements can be expected in the not-too-distant future.
Turnaround and cost reductions continue to be important and are particularly so for unconventional plays such as shale gas or tight gas (light tight oil) reservoirs, where 3D seismic is not yet as widely applied as in conventional settings. There is an increasing realization that these reservoirs are far less homogeneous than previously assumed. Seismic-based sweet spotting and well planning can add tremendous value to the staged development of unconventional reservoirs by accelerating the most productive wells and by avoiding uneconomic producers. In addition, microseismic monitoring of hydraulic fracturing or of thermal recovery techniques helps to improve the effectiveness of the required stimulation process and to manage associated integrity concerns.
I hope the selected papers for this feature provide interesting reading.
Recommended additional reading at OnePetro: www.onepetro.org.
SPE 161112 Optimized 3D Seismic Design Geometries for High-Density Surveys by Ghiath Ajlani, CGGVeritas, et al.
OTC 23700 New Opportunities From 4D Seismic and Lithology Prediction at Ringhorne Field, Norwegian North Sea by David H. Johnston, ExxonMobil, et al.
SPE 158753 Successful Application of 4D Seismic in the Stybarrow Field, Western Australia by Chris Hurren, BHP Billiton Petroleum, et al.
Hill, Robin Andrew (BHP Billiton Petroleum Americas Inc.) | O'Halloran, Gerry (BHP Petroleum) | Napalowski, Ralf (BHP Billiton) | Wanigaratne, Bimal (BHPBilliton) | Elliott, Alison Anne (BHP Billiton) | Jackson, Mark Alan (BHP Billiton Petroleum)
The Stybarrow Field is a moderate size biodegraded oil accumulation reservoired in early Cretaceous slope turbidite sandstones of the Macedon Formation in the Exmouth Sub-Basin offshore Western Australia. Excellent quality 3D seismic has enabled attribute mapping and probabilistic seismic inversion to be used to both estimate the net sand distribution of the reservoir and facilitate optimal well placement. The reservoir comprises excellent quality, but poorly consolidated, sand rich turbidites up to 20m thick. The field lies in >800m of water and has been developed with four near horizontal gravel packed production wells connected to an FPSO via sub sea trees and flowlines.
Water injection is required for pressure maintenance and produced gas is re-injected into the nearby Eskdale oil & gas field, the oil leg of which is produced via a single horizontal well. Pressure support is required from field start-up due to lack of aquifer support. Horizontal production wells with high productivity indices are required for optimal drainage. Downhole sand control is provided by a combination of open-hole gravel packs and sand screens.
Key subsurface challenges were faced in the development of the relatively thin reservoir containing biodegraded 22° API oil with little or no aquifer support. Lateral reservoir variations have important implications for connectivity and therefore the optimal drainage of such fields.
The Stybarrow project involves a nine well subsea development and a double hulled FPSO, the Stybarrow Venture, with capacity of approximately 80,000 barrels of oil a day. Oil came on stream in November 2007 and nameplate production was reached within weeks of first oil. The Stybarrow and Eskdale fields which make up the project have estimated recoverable oil reserves of 60 to 90 million barrels and estimated field life is 10 years.
This paper documents a multidisciplinary approach applied during the appraisal, development and early production life of the field. Static and dynamic data on a variety of scales (i.e. seismic, well data, bed boundary resistivity modeling, inter-well interference testing and early production performance) have been integrated into detailed 3D geological models, which have enabled a greater understanding of reservoir connectivity, as well as a better estimation of ultimate oil recovery.
The Stybarrow oilfield is located in Production License WA-32-L, some 56km northwest of Exmouth, offshore Western Australia (Figure 1). Water depth over the field is approximately 825m. The field lies near the southern margin of the Exmouth sub-basin within the overall Carnarvon Basin. Although the potential of the Stybarrow structure had been recognised on 2D seismic data, it was not high graded for drilling until seismic amplitude anomalies conforming approximately to structure were observed in a subsequent 3D seismic dataset acquired in 2000. The 3D seismic data indicated the prospect had many similarities to the nearby Laverda and Enfield discoveries.
Biodegraded (22° API) oil is trapped in Early Cretaceous, Berriasian age turbidite and debris flow sandstones deposited on a passive margin slope. The Stybarrow structure comprises a NE-SW trending tilted fault block forming a terrace within the westward plunging Ningaloo Arch (Figure 2a). The intersection of NNE/NE and E-W trending normal faults establish an elongate, triangular trap with dip closure to the east and structure dip of about 5 degrees. Top, base and bounding-fault seals are provided by claystones and siltstones of the overlying Muiron Member of the Barrow Group and mudstones of the underlying Dupuy Formation. Oil is sourced from claystones of the Dingo Formation.
Glinsky, Michael E. (BHP Billiton Petroleum, Houston, Texas) | Asher, Bruce (BHP Billiton Petroleum, Houston, Texas) | Hill, Robin (BHP Billiton Petroleum, Perth, Australia) | Flynn, Mark (BHP Billiton Petroleum, Perth, Australia) | Stanley, Mark (BHP Billiton Petroleum, Perth, Australia) | Gunning, James (CSIRO Petroleum, Clayton, Victoria, Australia) | Thompson, Troy (DownUnder GeoSolutions, Perth, Australia) | Kalifa, Jerome (Let It Wave, Ecole Polytechnique, Palaiseau, France) | Mallat, Stephane (Let It Wave, Ecole Polytechnique, Palaiseau, France) | White, Chris (Louisiana State University, Baton Rouge, Louisiana) | Renard, Didier (L'Ecole des Mines, Fontainebleau, France)
Successful appraisal and development of oil and gas fields requires the integration of uncertain subsurface information into multiple reservoir simulation models. This information includes seismic data, various types of well data, and geologic concepts. Over the past five years, a workflow has been developed by various organizations in conjunction with BHP Billiton Petroleum. This distinctive approach focuses first on building mesoscale reservoir models that can be constrained by seismic data (typically with a resolution up to the stratigraphic seismic loop scale, see Prather et al. 2000), then introducing the finer scale geologic concepts and well data needed for reservoir simulation models (stratigraphic 1st and 2nd order subseismic scale, where each order is about a factor of three in size) via a downscaling step that honors mesoscale model constraints. Uncertainty and correlations of the well and seismic measurements are always taken into account. In fact, they are necessary to be able to combine the various measurements. Bayesian probabilistic techniques are used extensively in this process. The result is an ensemble of reservoir simulation models that is consistent with all of the subsurface information.