Per Gunnar Folstad

Anisotropic traveltime tomography for depth consistent imaging of PP and PS data

P-to-S converted seismic waves have aroused significant interest in the oil exploration industry in recent years. When used in addition to PP data, they have proved valuable in reservoir characterization (e.g., lithology discrimination, determination of the fracture orientation) and in reservoir imaging (e.g., in case of the presence of gas, shale/sand discontinuities, multiple reflections). Combining this information for reservoir imaging requires PP and PS depth-migrated images that are correctly focused (i.e., resulting from the stack of common image point gathers characterized by flat seismic events) and consistent (i.e., PP and PS depth events end up at the same lateral and vertical positions). Methods for velocity model determination have therefore to ensure cofocusing (first requirement) and codepthing (second requirement). The velocity model determination method we propose is based on prestack traveltime tomography. In the following, we show that joint tomographic inversion of PP and PS data is very well suited to meet the two requirements, especially since anisotropy can be taken into account. Then, after describing the tomographic inversion methodology in some detail, we illustrate how we applied the joint PP and PS tomography to a 2D, 4C North Sea data set. Comparing isotropic and anisotropic inversion results reveals the necessity to take anisotropy into account for obtaining highly accurate depth-migrated images. Prestack traveltime tomography aims at determining a subsurface model that minimizes misfits between calculated traveltimes (computed by prestack ray tracing in the current model) and observed traveltimes (interpreted seismic events in prestack data). Traveltime information is generally not sufficient to ensure the uniqueness of the solution velocity model. Note that this underdetermination is not specific to traveltime tomography but to any kinematic methods, and is due to e.g., low-incidence angles at reflectors and to the nonillumination of some areas of the subsurface. Traveltime tomography offers the opportunity to find, …

Processing the Hod 3D multicomponent OBS survey, comparing parallel and orthogonal acquisition geometries

The Hod 3D multicomponent ocean-bottom seismic (OBS) survey was acquired to image the reservoir through a gas cloud. Data were acquired with shot lines both along the receiver cables (in-line or parallel shooting) and orthogonal to the receiver cables (cross-line shooting).

Simulation of 4D seismic signal with noise - illustrated by WAG injection on the Ula Field

Summary A method for simulation of time-lapse (4D) seismic response is presented and applied to data from the Ula Field. The method combines reflectivity data derived from the reservoir simulator with real 3D seismic data to predict the seismic response of a “monitor” 3D seismic survey. Noise extracted from real 4D difference data is added to the modeled data to compare the energy level of the noise to the predicted 4D signal. Scaling the noise level before adding the noise to the modeled data makes it possible to evaluate the effect of improved seismic repeatability on the 4D analysis. At Ula, where the reservoir rock is relatively insensitive to fluid and pressure changes, the noise of existing 4D seismic data is found to be at the same level as the strongest 4D signals predicted from the reservoir. A reduction in noise level of 50% or more would significantly improve the visibility of the signal.

Real-time data transfer to 3D model—maximizing wellbore value

Editors note: Most of the material in this article was presented at the 10th Abu Dhabi International Petroleum Exhibition and Conference in 2002 and originally published as SPE paper 78526. It is under copyright by SPE and is reprinted here with permission. Ula, a mature water-flooded oil field in block 7/12 of the Norwegian sector of the North Sea (Figure 1), is operated by BP Norge AS on behalf of partners DONG Norge AS and Svenska Petroleum AS. The oil accumulation is moderately deep (3350–3800 m TVDSS) and hot (150° C). The reservoir consists of upper Jurassic shallow marine sediments in a four-way dip closure above a salt structure (Figure 2). The field was discovered in 1976, and first oil was produced in 1986. Plateau oil production of 100–150 mbd was maintained until late 1993. Subsequent production has been about 25 mbd, sustained by infill drilling in the upper unit 1A reservoir and by injecting water and gas. A water-alternating gas (WAG) scheme has recently commenced. Figure 1. Location of Ula Field in the Norwegian sector of the North Sea. Figure 2. Cross-section through Ula Field. Vertical exaggeration approximately two-fold. Main reservoir (units 2,3) shaded in gray. Unit 1 reservoir is below the dashed line and above the gray shaded area. This paper describes recent experience on the last two unit 1A infill wells, which were geosteered, near-horizontal wells on the crest of the field structure. During the drilling of these wells, a real-time data link connected the Ula platform with BPs offices in Stavanger. This link enabled data from a directional drilling/LWD vendor and a mudlogging company to be loaded directly into BPs corporate subsurface database on a regular and automatic basis. The drilling and LWD data were also available to the entire drilling and completions team through a Web-based browser. The real-time …

Ekofisk PRM: A Look at Some of the Technology and How it Might Evolve

In this paper, we take a closer look at some of the technology used and the research carried out over the first two years on the Ekofisk PRM project. This includes QC issues for the acquisition; signal processing issues (such as 4D robustness of rotations; interference and VZ noise methods; surface consistent amplitude corrections); sensor performance and solutions to problems found; optimal imaging solutions such as FWI. Furthermore we report on the evolution of the Ekofisk operations in the coming months and discuss opportunities and possibilities arising via enhanced acquisition technology, improved processing and imaging, data management, and the potential for other reservoir oriented methods such as passive seismic monitoring.