Wavelet estimation in seismic convolved hidden Markov models
Inversion of seismic AVO-data is an important part of reservoir evalua- tion. These data are convolved but the convolution kernel and the associated error- variances are largely unknown. We aim at estimating these model parameters with- out using calibration observations in wells. This constitu tes the first step in socalled blind deconvolution. We solve the seismic inverse problem in a Bayesian setting and perform the associated model parameter estimation by an approximate marginal maximum likelihood method. A small test study indicate that bell-shaped wavelets with smooth edges are identified well, even for approximatio ns of low orders.
Approximate posterior distributions for convolutional two-level hidden Markov models
A convolutional two-level hidden Markov model is defined and evaluated. The bottom level contains an unobserved categorical Markov chain, and given the variables in this level the middle level contains unobserved conditionally independent Gaussian variables. The top level contains observable variables that are a convolution of the variables in the middle level plus additive Gaussian errors. The objective is to assess the categorical variables in the bottom level given the convolved observations in the top level. The inversion is cast in a Bayesian setting with a Markov chain prior model and convolved Gaussian likelihood model. The associated posterior model cannot be assessed since the normalizing constant is too computer demanding to calculate for realistic problems. Three approximate posterior models based on approximations of the likelihood model on generalized factorial form are defined. These approximations can be exactly assessed by the forward-backward algorithm. Both a synthetic case and a real seismic inversion case are used in an empirical evaluation. It is concluded that reliable and computationally efficient approximate posterior models for convolutional two-level hidden Markov models can be defined.
Organic geochemical characteristics and depositional setting of Tertiary organic-rich sediments from onshore Penyu Basin , eastern Chenor , Pahang , Malaysia
Poor knowledge of the organic facies characteristics of the eastern Chenor Pahang has made it remain an untapped potential in the Penyu Basin. Therefore, detailed geochemical and petrographic characterization of the Tertiary organic facies of the eastern Chenor area of the Penyu Basin was carried out to characterized its organic matter (OM) source input. Towards achieving the goal, this study focuses on determination of organic matters richness, type and origin as related to their paleoenvironmental conditions of the carbonaceous mudstone and shale using organic petrography combined with organic and inorganic geochemistry. The sedimentary succession is characterized by fine to coarse grained sandstone occurring in association with carbonaceous mudstone and shale in a predominantly fining upward sequence within a lacustrine environment. These facies are generally enriched in organic matter as indicated by the TOC results, hydrocarbon yield (S2) and extractible organic matter (EOM), suggesting significant hydrocarbon generation potential for the area.