Search

This chapter investigates the particular challenges for joint inversion in the context of hydrocarbon exploration. It reviews the current literature and introduces interesting approaches that have been developed in the context of hydrocarbon exploration and could potentially be used in other application areas as well. Joint inversion methods incorporating petro physical models of the reservoir can directly yield quantities of interest such as porosity and permeability, but have to be carefully tuned to the area under investigation. The chapter presents two detailed joint inversion case studies, one for subsalt imaging and one for sub basalt imaging. It also covers emulation of the forward calculation, a concept that can be applied generally in joint inversion, but has only been applied in hydrocarbon exploration. For a successful joint inversion, it is necessary to invert each dataset, construct different coupling approaches, and evaluate the impact on the final results.

Deep crustal constraint is often carried out using deterministic inverse methods, sometimes using seismic refraction, gravity and electromagnetic datasets in a complementary or "joint" scheme. With increasingly powerful parallel computer systems it is now possible to apply joint inversion schemes to derive an optimum model from diverse input data. These methods are highly effective where the uncertainty in the system is small. However, given the complex nature of these schemes it is often difficult to discern the uniqueness of the output model given the noise in the data, and the application of necessary regularization and weighting in the inversion process means that the extent of user prejudice pertaining to the final result may be unclear. We can rigorously address the subject of uncertainty using standard statistical tools but these methods also become less feasible if the prior model space is large or the forward simulations are computationally expensive. We present a simple Monte Carlo scheme to screen model space in a fully joint fashion, in which we replace the forward simulation with a fast and uncertainty-calibrated mathematical function, or emulator. This emulator is used as a proxy to run the very large number of models necessary to fully explore the plausible model space. We develop the method using a simple synthetic dataset then demonstrate its use on a joint data set comprising first-arrival seismic refraction. MT and scalar gravity data over a diapiric salt body. This study demonstrates both the value of a forward Monte Carlo approach (as distinct from a search-based or conventional inverse approach) in incorporating all kinds of uncertainty in the modelling process, exploring the entire model space, and shows the potential value of applying emulator technology throughout geophysics. Though the target here is relatively shallow, the methodology can be readily extended to address the whole crust.

We present the first application of Stochastic Heterogeneity Mapping based on the band-limited von Kármán function to a seismic reflection stack of a Mediterranean water eddy (meddy), a large salt lens of Mediterranean water. This process extracts two stochastic parameters directly from the reflectivity field of the seismic data: the Hurst number, which ranges from 0 to 1, and the correlation length (scale length). Lower Hurst numbers represent a richer range of high wavenumbers and correspond to a broader range of heterogeneity in reflection events. The Hurst number estimate for the top of the meddy (0.39) compares well with recent theoretical work, which required values between 0.25 and 0.5 to model internal wave surfaces in open ocean conditions based on simulating a Garrett-Munk spectrum (GM76) slope of −2. The scale lengths obtained do not fit as well to seismic reflection events as those used in other studies to model internal waves. We suggest two explanations for this discrepancy: (1) due to the fact that the stochastic parameters are derived from the reflectivity field rather than the impedance field the estimated scale lengths may be underestimated, as has been reported; and (2) because the meddy seismic image is a two-dimensional slice of a complex and dynamic three-dimensional object, the derived scale lengths are biased to the direction of flow. Nonetheless, varying stochastic parameters, which correspond to different spectral slopes in the Garrett-Munk spectrum (horizontal wavenumber spectrum), can provide an estimate of different internal wave scales from seismic data alone. We hence introduce Stochastic Heterogeneity Mapping as a novel tool in physical oceanography.

A small volume (117 cu-inch) seismic source producing signal predominantly in the 150-200 Hz frequency window was used during the GO calibration experiment in the Gulf of Cadiz (April-May 2007). The data show the small scale (< 10 m in the z direction) internal structure of the ocean. High-resolution images display seismic reflectors that often appear as distinct, horizontal, short (similar to a few hundred meters to a few km long) segments, lying at different depths, while low-resolution (similar to 20 to 30 Hz) display long, horizontal reflectors (similar to a few tens of km), sometimes linked by short, apparently "dipping" segments. The present data suggest that this apparent dipping effect is due to the insufficient separation power (similar to lambda/4) of the low resolution data. Improving high resolution acquisition systems hence appears to be a critical challenge to understand the seismic response of the ocean. Citation: Geli, L., E. Cosquer, R. W. Hobbs, D. Klaeschen, C. Papenberg, Y. Thomas, C. Menesguen, and B. L. Hua (2009), High resolution seismic imaging of the ocean structure using a small volume airgun source array in the Gulf of Cadiz, Geophys. Res. Lett., 36, L00D09, doi:10.1029/2009GL040820.

The observation of spatial and temporal dynamics of the ocean is fundamental to understand global and regional aspects of water mixing. Physical oceanography has traditionally observed ocean structures with in situ measurements, often limited in temporal and/or spatial resolution. In exploration seismology a set of techniques has been developed over the last decades to image and characterize the physical properties of sub-seafloor structures by inversion methods at high horizontal resolution. The two different fields have made contact in seismic oceanography where the well developed methods of marine reflection seismology have been applied to the dynamic ocean. However, one aspect, so far ignored in seismic oceanography, is the dynamical, temporally varying nature of water structures. Here we show that it is possible to estimate temporal variations of reflectors in water structures as an inversion parameter. The new dynamic property reflector movement velocity gives an additional parameter to characterize ocean water dynamics.

The seismic reflection profile is the convolution of the seismic acquisition impulse response and the target impedance contrasts. In the ocean, these contrasts are mainly determined by the widths and gradients of the temperature transitions between the different water masses. Hence seismic oceanography profiles are sensitive to the frequency bandwidth of the seismic acquisition system. We tested a novel seismic source that allowed us to simultaneously profile the ocean with differing impulse responses. We show that frequencies ∼20 Hz are best to delineate large impedance contrasts that occur over a vertical scale of several tens of meters whereas frequencies ∼80 Hz image the boundaries of layers of around 10 m. We demonstrate a towed acquisition system that can operate from a research vessel to give a bandwidth from 10 to 120 Hz that could, if required, be modified to provide frequencies up to 200 Hz.