Uncertainties in marine controlled source electromagnetic (CSEM) data consist of two independent parts: measurement noise and position uncertainties. Measurement noise can be readily determined using stacking statistics in the Fourier domain. The uncertainties due to errors in position can be estimated using perturbation analysis given estimates of the uncertainties in transmitter-receiver geometries. However, the various geometric parameters are not independent (e.g. change in antenna dip affects antenna altitude, etc.) so how uncertainties derived from perturbation analysis can be combined to derive error-bars on CSEM data is not obvious. In this study, we use data from the 2009 survey of the Scarborough gas field to demonstrate that (a) a repeat tow may be used to quantify uncertainties from geometry, (b) perturbation analysis also yields a good estimate of data uncertainties as a function of range and frequency so long as the components are added arithmetically rather than in quadrature, and (c) lack of a complex error structure in inversion yields model results which are unrealistic and leads to “over-selling” of the capabilities of CSEM at any particular prospect.
In May-June of 2009, we carried out a magnetotelluric (MT) and controlled source electromagnetic (CSEM) survey over the Scarborough gas field on the Exmouth plateau off the northwest coast of Australia. At 144 receiver deployments, this is the largest academically collected CSEM dataset to date. The main purpose of this study is to provide a demonstration dataset over a well-studied area and to drive future development in EM methods by placing this data in the public domain. In this paper, we present first results of CSEM data processing and 1D inversion from phase 1 of the survey.
The Exmouth plateau is a passive-margin between continental and oceanic crust left over from the break-up of Australia and India, and is surrounded on three sides by oceanic crust at abyssal depths. Since the Mesozoic era, the plateau has undergone a complex sequence of fracture, extension, uplift, truncation, and subsidence (Exon et al., 1982, Mutter and Larson, 1989, Lorenzo et al., 1991, Driscoll and Karner, 1998). The present plateau is covered by a number of mostly horizontal sedimentary layers of resistivities varying between 1 and 2 Ωm. The gas reservoir is a 20-40 m layer residing between 1900 and 2000 m depth with a moderate resistivity of 25 Ωm and is overlain by several thin layers of lower gas saturation with resistivities of 5-10 Ωm. An interesting feature, and one which presents a challenge for CSEM hydrocarbon exploration, is the presence at ~1500 m of the resistive Gearle siltstone formation with a thickness of ~100 m in the survey area and a resistivity of 3 Ωm (Veevers and Johnstone, 1974). The resistivity-thickness product of the Gearle is similar in magnitude to the reservoir, so we expect this confounding resistor to present a nice challenge for CSEM modeling and inversion methods. The CSEM method is primarily sensitive to resistive structures (Cox, 1981, Cox et al., 1986) and over the past decade has found increasing use in hydrocarbon exploration (Constable and Srnka, 2007). However, the field is relatively new, so academic quality codes for modeling and inversion are still being developed; e.g. (Li and Key, 2007, Key, 2009). Many of the supposedly more advanced inversion codes presented in publications and presentations over the past decade are held as the intellectual property of for-profit corporations and are therefore not open to inspection or operation by the general public. We believe that such private advancement deters the field as a whole. So our primary goal for this survey is to collect a high quality dataset which can be used to expand the CSEM method. It is our intention to release the data into the public domain in conjunction with inversion studies using academically available codes. We hope that the availability of a standard dataset with inversion results from open-source codes will provide a measure of quality by which the private codes can be evaluated and will push the development of the CSEM method as a whole back into the public domain.