Exploration Geophysics - Volume 39, Issue 2, 2008

Deepwater Taranaki is investigated for its petroleum potential, using all available seismic data tied to shallow-water wells. It contains up to 10 km of sediment. An early rift sequence is overlain by a large Late Cretaceous delta, which culminates with the mid-Campanian Rakopi Formation coal measures. This sequence marks the break-up unconformity following the start of Tasman Sea spreading. A passive margin succession follows as the New Zealand mini-continent gradually subsided, with sediments becoming gradually finer grained until carbonates dominate during the Oligocene. Initiation of the present plate boundary around the start of the Miocene, 25 million years ago, caused uplift and renewed clastic deposition in the form of spectacular channel and turbidite complexes.

The present reconnaissance seismic grid indicates at least six subtle structures that are each large enough to contain a billion barrels of oil or several trillion cubic feet of gas, suggesting that the first drilling targets may be Late Cretaceous fluvial and marine sands draped across gentle basement structures. Cretaceous structures are commonly overlain by Miocene channel and turbidite sands that are also draped across underlying highs. The similar, but much smaller structures of Tui, Amokura, and Pateke, on the Taranaki shelf, are currently being produced by AWE. Future discoveries are likely closer to the shelf edge and ultimately the larger prizes will be sought in deeper water.

The Enfield rock physics model was constructed to enable 4D feasibility studies and interpretation of the 2007 Enfield 4D seismic monitor survey. The rock physics model links reservoir static and dynamic parameters to impedances, using log data from five wells in the field, laboratory core measurements taken from cores on Enfield and neighbouring fields, and theoretical rock models from the literature. The reservoir is modelled by a sand-shale mix: sand properties are described using a modified critical porosity model whereas shale properties are generated from log data averaging. The dynamic properties in the model include saturation and pressure. Saturation is modelled using Gassmann’s formula assuming homogeneous mixing. The reservoir sand velocity-pressure relationship is described by an empirical model fitted to dry core plug measurements. An assessment of the effect of uncertainty is included for both the saturation and pressure elements of the model. The resultant rock physics model was used before the acquisition of the seismic monitor survey to assess the likelihood of detecting a 4D seismic signal only 7 months after production start-up. Our modelling results indicate that the strong pressure build-up around the water injectors would result in a detectable 4D seismic signal and this prediction is confirmed by the successful 4D seismic monitor data acquired in 2007. The rock physics model has been validated against the 4D monitor data and is being used to quantify the 4D interpretation, linking the observed 4D response back to predicted pressure and saturations changes in the field.

Well log and rock sample data from fourteen offshore petroleum exploration wells have been successfully up-scaled and integrated using facies classification. Over 100 rock samples were categorised into six petrofacies classes based on their composition and texture. Cluster analysis was used to classify well log data into five electrofacies units, after careful conditioning and selection of input logs. The result is a direct link between well logs and rock samples. Electrofacies profiles clearly illustrate stratigraphic information previously hidden in the well logs. In addition, well log acoustic rock property relationships based on the new electrofacies classes are found to be better constrained than lithology-based models.

Previous facies studies either have been applied at a field scale or have had conventional core for petrofacies calibration. In this paper, I illustrate how facies analysis can be successfully applied at a regional scale with only sidewall sample calibration. Particular attention was given to conditioning the cluster analysis input logs by removing all effects of fluid fill and mechanical compaction, which varied significantly across the study area. A lesson learned from the project was that it is easy to generate misleading results with cluster analysis, so care was taken to select only the most appropriate input logs, and to thoroughly quality control the output electrofacies.

Density plays an important role in coal resource estimation and reconciliation, as well as in defining coal quality. Current practice employs direct density measurements on widely spaced core samples, rather than utilising abundant geophysical logging data. This is mostly due to the perception that the precision and accuracy of density estimation from geophysical logs is unsatisfactory. This paper demonstrates that the density wireline log, supported by other geophysical logs, provides a reliable direct measurement of in-situ coal density. We have produced a consistent and reliable correlation of geophysical log density with a laboratory-derived density to within an accuracy of ±3%. This is achieved through careful constraints such as compensating for lost pore spaces and moisture to bring the laboratory relative density closer to in-situ environmental conditions, matching the laboratory sample depths with geophysical logs, excluding thin, boundary, and stone-band samples from the dataset, and calibrating the geophysical density with laboratory testing data and other geophysical logs by linear regression or Radial Basis Function and Self-Organised Mapping techniques. In addition, we also illustrate that the improved geophysical log density can be used for coal quality estimation.

The VTEM system developed and operated by Geotech Limited and Geotech Airborne Limited is a central loop configuration system lending itself to many traditional ground interpretation strategies. One of these is the S-layer (thin, conductive layer) differential transform that is used to generate resistivity-depth sections. An empirical study indicated that delineating conductors in a conductive half space necessitates the implementation of a scale factor in order to obtain the correct depths and conductivity values when applying the S-layer differential transform.

Based on an empirical approach, there was found to be an infinite number of depth correction factors that will still yield acceptable conductivity values, and the need arose to explain the origin of this discrepancy and to find the correct depth correction factor. A correction strategy was followed, based on scaling results to yield exact conductivities when applied to half-space models. Assuming that the equivalent filament for the S-layer behaviour, as with the equivalent filament for the half-space behaviour, does not coincide with the electric field maxima in the subsurface led to a plausible depth correction factor which was validated on various synthetic models.