Rocksource solves the Luva enigma

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The Luva Field was discovered ten years ago (1997) when BP hit gas in deep water (1274 m) in the Vøring Basin of the Norwegian Sea. In 2003, just after emgs (www.emgs.com) were established, a SBL line was acquired to test the response from the Luva discovery. This line was one of many 2D lines that emgs acquired in the early phase of the development of the method.

While most of these lines proved that the technology worked, no significant EM anomaly was detected from Luva. This was quite disappointing, partially because the technology appeared to be unreliable and partially because sceptics latched on to this one failure to dismiss the entire approach. For Rocksource this was simply seen as a challenge.

As part of an evaluation study, Rocksource scientists started by looking at the reservoir section in detail. Although the reservoir is of generally high quality, well logs show significant anisotropy in the resistivity, with peaks up to 200 ?m and several sections with less than 10 ?m resistivity. Low overall target resistivity will significantly reduce the electromagnetic response. With synthetic modelling, based on a realistic target and background geology, Rocksource scientists were able to show that the response from the Luva discovery, when compared to background resistivity, will be less than 10%, compared to a response of 250% from the Troll Field reservoir.

Based on the reservoir studies combined with synthetic modelling, Rocksource scientists went on to solve the enigma of the presumed false-negative EM response from Luva. The starting point for the analyses was to investigate synthetic data. A representative 3D model was built based on a geological understanding of the area. A synthetic 3D CSEM dataset was then generated and inverted. As a starting point for the inversion, no constraints were used. The results clearly indicate that the Luva hydrocarbon column cannot be expected to be detected using a basic approach.

The next step was to do a similar inversion with real data as input. The inversion result was very similar to that of the synthetic data, indicating that the geological model was representative of the real geology and further demonstrating that the Luva discovery could not be identified using this approach.

The next step in the analyses was to provide regional constraints based on the geological understanding of the area. Seismic data were particularly important at this stage as they enabled resistivity values to be attributed to particular intervals. This part of the process is time-consuming and requires detailed geological and geophysical knowledge of the area under investigation.

By applying the constraints, the inversion was guided towards what the geoscientist considers to be a more appropriate solution. The integrated approach applied to the synthetic data indicated that the Luva discovery could be identified using this workflow provided that the input geological model was representative.

The last stage involved using the same constrained approach as for the synthetic example, but this time with real data. Again, the inputs to the constraints were taken from the interpretation of regional seismic data and a sound geological understanding of the area. No well information was used, and no constraints were used for the target itself (including parameters such as geometry, depth, thickness, lateral extent and resistivity).

The final result was that the Luva discovery was clearly identified with a pronounced resistivity anomaly. The similarities to the synthetic example suggest that the synthetic model is realistic and consistent with observations from the real data.

The integrated approach to solving the challenge makes perfect scientific sense in that all pertinent data that are made available. Rocksource then use their tailor-suited and proprietary inversion algorithms to process the data. This by no means represents a manipulation of the analyses. Rather, a sound geological understanding of an area is used in the analyses, and this is what explorationists are trained to do. EM data represent one more piece of information, just as the well data and seismic data are. No explorationist would treat seismic data in isolation, and similarly, EM data should not be treated independently either.

Advanced processing and inversion are normally required to fully understand the data. In complex settings, it is essential to use all the available information such as input from seismic data, borehole data as well as a sound geological understanding of an area. The Luva case demonstrates elegantly the potential that this technology has in future hydrocarbon exploration, when applied correctly.

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