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In an attempt to understand the environment of the Precambrian weathering at Rispond, and compare it with weathering processes taking place at the present time, samples weathered to different degrees have been taken at various distances immediately below the Cambrian Unconformity. These samples have been subjected to chemical analysis by X-ray fluorescence spectometry and wet analysis, and to mineralogical analysis by X-ray diffraction and polarised light microscopy. Interpretation of these results indicate that the samples represent a weathering profile (although not necessarily an unchanged one as these rocks have been subjected to a maximum temperature of 250°C during burial subsequent to the deposition of the Cambrian strata). This is inferred from the minerals present in the soil, the nature of the chemical changes observed, the similarities of the data on the Kronberg weathering diagram to those of present-day weathering, and the position of the profile immediately below the unconformity. Further interpretation of the results in terms of the thermodynamic properties of the minerals present in the profile, the chemical reactions believed to have taken place, the geological evidence and a survey of the chemical composition of present-day surface waters leads to the conclusion that the rocks below the Cambrian Unconformity at Rispond represent a fossil soil profile. These rocks contain pyrophyllite, considered to have been formed by low-grade metamorphism rather than by weathering. Three possible modes of origin have been considered, and that involving the weathering of potassium feldspar to kaolinite alone in an acid environment rejected. The two mechanisms involving the weathering of the feldspar to illite in an arid alkaline environment with restricted drainage are considered to be more likely. The illite produced in these mechanisms was further weathered to produce, in the one case, kaolinite, and in the other one, potassium beidellite as a mixed layer mineral with illite. These two mechanisms can be mixed in any proportion, the exact amount of potasium beidellite present depending upon the relative thermodynamic stabilities of kaolinite and beidellite. As the latter is unknown, further accuracy cannot be achieved at present. The presence of abundant potassium feldspar in the Fucoid Beds, and the existence of trace fossil planolites in such rocks as well as the temperature to which they have been heated (about 250°C) suggested the possible existence of an ammonium feldspar in the area. Therefore, a method to measure the amount of ammonia content in these rocks has been designed. The results of twenty-two samples from the Cambro-Ordovician succession of N.W. Scotland analysed by this method show that the ammonia content is very low. If all the ammonia is present as an ammonium feldspar (buddingtonite), it represents about 0.3% of the mineral in the shales and even less in other rock types.

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This thesis describes how I have researched and developed new methods for the prediction of rock physical properties using genetic algorithms and fuzzy logic (GAFL).  These techniques are improvements on conventional methods providing two original but dissimilar tools for formation evaluation and reservoir characterisation. The premise behind the use of fuzzy logic in this context is that a reservoir can be broken down into several lithotypes, each having characteristic statistical distributions for electrical log values.  Fuzzy logic attempt to uncover the relationships between these distributions.  Genetic algorithms use a feedback technique that assumes a continuous functional relationship between the electrical log values and rock properties, generating and testing equations that fit predicted and observed responses.  Complex non-linear equations are “evolved” until the best fit is obtained.  Genetic algorithms provide the functional form of the equation as well as the constant parameters of the relationship. I have modified conventional GAFL techniques so that they can be more precisely calibrated and applied to geoscience problems more successfully.  This research analysed the characteristics of large data sets from several North Sea and Middle Eastern fields, and led to the design of software that automatically calibrates GAFL in a way that is less sensitive to noise and data outliers.  I describe the applications of these new techniques to permeability, litho-facies, porosity and shear velocity prediction;  the repair of poor electrical logs and the modelling of shaly sand equations. Permeability governs the movement of fluids through reservoir rocks and is therefore a critical input into reservoir models.  Permeability estimation is extremely challenging, as it is difficult to measure directly using current sub-surface logging technology.  GAFL was applied to predict permeability in the Northern North Sea oil fields.  The newly developed software provides an important and visual indication of the uncertainty associated with the predicted permeabilities.

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No description available.