The seismic reflection survey was shot to elucidate two important topics relating to Hot Dry Rock (HDR) research: (1) The structure of the granite at depths between 4 and 8 km, as an HDR pilot scheme would require drilling to a depth of about 6km within the granite. The presence of any large scale geological structure within the granite at this depth could affect the behaviour of an HDR reservoir, both in terms of its formation and its long term behaviour. The results of the survey show that on a broad scale the granite appears very homogenous. (2) Knowledge of the shape of the granite is important if the available thermal resource is to be assessed. The seismic survey was shot not just over granite outcrop, but also over ''killas'' (Devonian-Carboniferous lower Greenschist facies argillites and arenites with minor basic volcanic and volcaniclastic intercalactions), to try to better determine the shape of the sides of the granite. The main geophysical technique which has been used to assess the overall spaceform of the granite is gravity. A large gravity dataset now exists and 3-dimensional models of the gravity have been produced. If the shape of the granite below the seismic lines can be determined from the seismic reflection survey data then this can be checked against the gravity model and used to improve it. The seismic results show good agreement with the gravity model where the killas overlying the granite achieves an appreciable thickness. (author).
P294 OPTIMAL FOUR GEOPHONE CONFIGURATION VECTOR FIDELITY AND LONG-TERM MONITORING Introduction 1 The increased use of 3D and now 4D multi-component seismic reflection imaging methods and their application to reservoir monitoring means that ever greater amounts of information and detail are being sought from seismic reflection data. This in turn requires data of increased quality and reliability. Now with the advent of life of field seabed seismic systems these requirements are becoming even more pressing. As well as improving the performance of any permanent system its performance over time must also be closely monitored and if it is found to
The interpretation of a cloud of earthquake hypocenters in terms of causative structures is not a simple task. Locations are subject to uncertainties, which will not be the same for every earthquake. The data should therefore not be interpreted simply by inspection, which is difficult in the case of three‐dimensional data anyway. Instead, we propose using the location uncertainties as a guide in processing the data. Earthquake locations are moved inside their uncertainty or confidence ellipsoids until a simplified picture of the earthquake cloud is obtained, which can then be interpreted in terms of some simplified structure such as faults. The aim of the approach is to give the simplest possible structure that is consistent with all the location and confidence ellipsoid data. The method is applied to three synthetic sets of data. These illustrate the potential and limitations of the method. Application to a real earthquake data set from Rabaul Caldera in Papua New Guinea gives an image of the caldera ring fault that suggests departures from the simple ring‐fault structure previously assumed. Sensitivity analysis on the Rabaul data shows that the method is not unduly sensitive to the assumptions that have to be made in applying it.
A new method for improving relative locations of clustered earthquakes is presented and applied to a suite of microearthquakes induced by hydraulic frac- turing. The method is based on the assumption that clustering of earthquake hypo- centers is obscured by the uncorrelated scatter of individual hypocenters. The method is implemented as an additional constraint in a Joint Hypocenter Determination (JHD) scheme. The method shifts event hypocenters toward the center of mass of the events within some volume surrounding the event location if the RMS misfit between pre- dicted and measured arrival times does not increase significantly. The method uses the same basic assumption of Jones and Stewart (1997), which is that there is greater clustering in actual earthquake locations than there is in locations determined using conventional techniques. Our method differs in that it is implemented as part of the JHD process so it operates on raw travel-time data rather than on derived hypocenters. The method produces hypocenters from a demonstration field dataset that are similar to those obtained by Phillips et al. (1997), from time-consuming precise manual repicking of relative arrival times of events. The clustering constraint can easily be incorporated as an additional constraint in earthquake location/velocity tomography codes and may lead to improved velocity structure determination and earthquake location pattern identification and interpretation.
