Cedric Griffiths

High-Frequency Sequence Stratigraphy Using Syntactic Methods and Clustering Applied to the Upper Limestone Coal Group (Pendleian, E1) of the Kincardine Basin, United Kingdom

We define a distance between sedimentary successions to compare their dissimilarity formally. Distance definition is based on attributed syntactic representation. One-dimensional successions can be represented by a string of lithofacies symbols sequentially or vertically. Each symbol can also have a vector of attributes that can provide other information on lithofacies such as thickness. The distance of any two successions is then defined consisting of its syntactic and attribute subdistances. Syntactic distance measures difference of vertical lithofacies change between two successions and attribute distance measures difference of thickness of corresponding lithofacies. Clustering is used to test validity of distance definition and its potential application to analysis of cycle-dominated sedimentary successions. Example is from the Namurian-A succession in Kincardine basin, central Scotland. There are 56 cycles in intervals of about 300 m each in two boreholes. Recognition of intermediate cycles depends on correctly determining of types of these short cycles and their vertical stacking pattern. Intermediate cycles have better potential in high-resolution stratal correlation regionally. Syntactic clustering results show that 56 short cycles can be classified into four groups with distinctive geological interpretation, which further helps reveal hierarchical cyclic architecture of the whole succession.

Effective stress coefficient for P- and S-wave velocity and quality factor in sandstone, Example from Cooper Basin-Australia

Summary The velocities and quality factors of compressional and shear waves have been measured at ultrasonic frequencies in Cooper Basin sandstone under a rang of pore pressure and confining stress using a pulse-echo technique. The effective stress coefficient, n, is found to be less than 1 for both velocities and quality factors in the Cooper Basin sandstone. The pore pressure sensitivity of wave velocities decrease ( n approaches one) with the increase of differential pressure. In contrast, the effect of pore pressure on both P- and S-wave quality factors increase ( n decreases) with increasing differential pressure. The strong influence of pore pressure on Q p and Qs is attributed to behavior of pore filling and grain coating clay minerals.

Syntactic Simulation of 1-D Sedimentary Sequences in a Coal-Bearing Succession Using a Stochastic Context-free Grammar

ABSTRACT Syntactic pattern recognition (SPR) provides a new symbolic computing paradigm that has a great potential for application in sedimentologic and stratigraphic theory. In an SPR system, a formal language consists of a set of sentences; each sentence is a string of terminal symbols (or words); a grammar is used to characterize syntactic structures of the language, which tells whether or not a specific sentence belongs to the language. A language represents a class of patterns that are similar to each other in some sense. A sentence from the language then represents an individual pattern of the class. The grammar defines the legality of members of the class in general. There are several key subdomains in this methodology, such as grammar inference, language generation or sim lation, and language parsing. The objective of this paper is to show the possibility of using geological knowledge, obtained by domain experts (here sedimentologists), to construct valid grammars characterizing the vertical structure of different orders of sedimentary sequences, by applying the methodology to the analysis of a coal-bearing succession of the upper Limestone Coal Group, Pendleian (E1) in the Kincardine basin, Central Scotland. First, complete successions from two boreholes are encoded into syntactic strings of lithofacies symbols. Five groups of different high-frequency sedimentary sequences have been recognized. These high-frequency sequences combine to form a lower-frequency sequence. This geological knowledge is used in a heuristic sense to manually construct grammars f r each of the five groups of sequences and for the whole succession. Finally, the constructed grammars, together with a thickness simulation for each lithofacies, are used to generate similar sedimentary sequences to test the validity of the grammars and therefore their further application to a formal analysis of sedimentary sequences. Comparison of simulated sequences with real sequences indicates that SPR is an encouraging technique in the analysis of sedimentary sequences.

A new approach to reservoir heterogeneity modelling: conditional simulation of 2-D parasequences in shallow marine depositional systems using an attributed controlled grammar

Abstract An attributed controlled grammar (ACG) has been formally used to represent the parasequences of a clastic shallow-marine system. The lithofacies distribution has been conditionally simulated in two dimensions using the ACG. In knowledge representation, the ACG has been shown to have several advantages over context-free, programmed and attributed grammars. The ACG for the parasequences is manually constructed by domain experts based on a conditioning dataset, combined with related sedimentological knowledge. The dataset includes several geological sections measured from outcrops and interpreted from boreholes. A parasequence is decomposed into coastal plain, foreshore, upper shoreface, lower shoreface and offshore facies tracts and their boundaries. Within each tract, lithofacies distribution is described by the facies transition relationship, which can be constructed directly from the dataset and adjusted in terms of related sedimentological knowledge. The boundaries between the tracts are represented by point chains, whereas the facies transitions are controlled by a transitional probability matrix and both vertical and horizontal extensions of the corresponding lithofacies. The simulation results show the following features: (1) the simulation honors the conditioning dataset, (2) the lithofacies distribution simulated from the ACG shows increased variability compared to traditional interpolations between geological sections and (3) the simulated lithofacies distribution is controlled mainly by the uncertainty of the vertical and horizontal extension of each lithofacies, which cannot usually be obtained directly from the conditional dataset, and is not formally considered in traditional geological correlation and interpretation. Work is underway to quantify such lateral and vertical extension in present-day systems.

Integration of Stratigraphic & Rock Physics Models to Generate Synthetic Seismic Data

Stratigraphic forward modelling (SFM) is an important subsurface modelling method. A numerical SFM program, such as the Sedsim software used in this study, is able to quantitatively model the sedimentation process with time in order to predict rock properties away from well data. Although numerical SFM is a powerful technique, it is important to quantify and minimise the uncertainty in the resultant stratigraphic model. This uncertainty can be reduced by producing synthetic seismic traces from the results of the stratigraphic model. This simulated seismic may then be compared to observed seismic over the same area and the parameters of the stratigraphic model modified based on the results of the comparison. In order to generate synthetic seismic from the results of a stratigraphic model, sediment properties from the stratigraphic model must be converted to acoustic properties. This becomes challenging at inter-well locations, or locations with little or no well control. Fortunately, such conversion can be achieved by the application of a suitable rock physics model even at those challenging locations. The integration of a Sedsim stratigraphic model and the Velocity-Porosity-Clay (VPC) rock physics model in the Cornea field, Browse Basin, Australia shows the importance of integrating geological and geophysical methods in order to reduce uncertainty when predicting subsurface properties.