<p>Many hydrocarbon reservoirs are situated in barren sequences that display poor stratigraphic control. Correlation between the wells can become extremely difficult and traditional correlation techniques can prove to be inadequate. Past studies have shown that trace and major element concentrations can be used as a correlation tool. This practice of using geochemical fingerprints to characterize between wells is called Chemostratigraphic analysis. (Pearce et al, 1999) Chemostratigraphy has been recognized as a very important correlation technique as it can be used for rocks of any age, in any geological setting as well as sequences that are traditionally defined as barren. Chemostratigraphic analyses can be used as a means of getting rid of ambiguities within data produced by traditional correlation methods such as Biostratigraphy, Lithostratigraphy and Geophysical Logging. In areas where stratigraphic data is not available it can be used to construct correlation frameworks for the sequences found in the area. The motivation behind this study is that the research is not only worthy of academic investigation, but can also provide the industry with new insights into areas that were previously misunderstood because traditional correlation methods were not adequate. The study area, the Orange basin, is located offshore South Africa and is largely underexplored. The basin, that hosts two gas field namely the Ibhubesi and the Kudu gas fields, has large potential but in the past has not been given due attention with only 34 wells being drilled in the area. The Orange basin has recently been the topic of investigation because of the belief that it may be hosts to more hydrocarbons. This study will utilise Chemostratigraphy to attempt to provide geological information on this relatively under-explored basin. The aim of this research study is to produce a chemostratigraphic framework -scheme for the Orange Basin in order to facilitate reservoir scale interwell correlation. The Objectives of this research study will be to identify chemostratigraphic units or indices, to prove the adequate use of chemostratigraphy as an independent correlation technique and to integrate the chemostratigraphy and petrophysical characteristics of the four wells to facilitate lithological identification.</p>

Rock type is a key concept in modern reservoir characterization that straddles multiple scales and bridges multiple disciplines. Reservoir rock classification (or simply rock typing) has been recognized as one of the most effective description tools to facilitate large-scale reservoir modeling and simulation. This dissertation aims to integrate core data and well logs to enhance reservoir description by classifying reservoir rocks in a geologically and petrophysically consistent manner. The main objective is to develop scientific approaches for utilizing multi-physics rock data at different time and length scales to describe reservoir rock-fluid systems. Emphasis is placed on transferring physical understanding of rock types from limited ground-truthing core data to abundant well logs using fast log simulations in a multi-layered earth model. Bimodal log-normal pore-size distribution functions derived from mercury injection capillary pressure (MICP) data are first introduced to characterize complex pore systems in carbonate and tight-gas sandstone reservoirs. Six pore-system attributes are interpreted and integrated to define petrophysical orthogonality or dissimilarity between two pore systems of bimodal log-normal distributions. A simple three-dimensional (3D) cubic pore network model constrained by nuclear magnetic resonance (NMR) and MICP data is developed to quantify fluid distributions and phase connectivity for predicting saturation-dependent relative permeability during two-phase drainage. There is rich petrophysical information in spatial fluid distributions resulting from vertical fluid flow on a geologic time scale and radial mud-filtrate invasion on a drilling time scale. Log attributes elicited by such fluid distributions are captured to quantify dynamic reservoir petrophysical properties and define reservoir flow capacity. A new rock classification workflow that reconciles reservoir saturation-height behavior and mud-filtrate for more accurate dynamic reservoir modeling is developed and verified in both clastic and carbonate fields. Rock types vary and mix at the sub-foot scale in heterogeneous reservoirs due to depositional control or diagenetic overprints. Conventional well logs are limited in their ability to probe the details of each individual bed or rock type as seen from outcrops or cores. A bottom-up Bayesian rock typing method is developed to efficiently test multiple working hypotheses against well logs to quantify uncertainty of rock types and their associated petrophysical properties in thinly bedded reservoirs. Concomitantly, a top-down reservoir description workflow is implemented to characterize intermixed or hybrid rock classes from flow-unit scale (or seismic scale) down to the pore scale based on a multi-scale orthogonal rock class decomposition approach. Correlations between petrophysical rock types and geological facies in reservoirs originating from deltaic and turbidite depositional systems are investigated in detail. Emphasis is placed on the cause-and-effect relationship between pore geometry and rock geological attributes such as grain size and bed thickness. Well log responses to those geological attributes and associated pore geometries are subjected to numerical log simulations. Sensitivity of various physical logs to petrophysical orthogonality between rock classes is investigated to identify the most diagnostic log attributes for log-based rock typing. Field cases of different reservoir types from various geological settings are used to verify the application of petrophysical rock classification to assist reservoir characterization, including facies interpretation, permeability prediction, saturation-height analysis, dynamic petrophysical modeling, uncertainty quantification, petrophysical upscaling, and production forecasting. / text

<p>Many hydrocarbon reservoirs are situated in barren sequences that display poor stratigraphic control. Correlation between the wells can become extremely difficult and traditional correlation techniques can prove to be inadequate. Past studies have shown that trace and major element concentrations can be used as a correlation tool. This practice of using geochemical fingerprints to characterize between wells is called Chemostratigraphic analysis. (Pearce et al, 1999) Chemostratigraphy has been recognized as a very important correlation technique as it can be used for rocks of any age, in any geological setting as well as sequences that are traditionally defined as barren. Chemostratigraphic analyses can be used as a means of getting rid of ambiguities within data produced by traditional correlation methods such as Biostratigraphy, Lithostratigraphy and Geophysical Logging. In areas where stratigraphic data is not available it can be used to construct correlation frameworks for the sequences found in the area. The motivation behind this study is that the research is not only worthy of academic investigation, but can also provide the industry with new insights into areas that were previously misunderstood because traditional correlation methods were not adequate. The study area, the Orange basin, is located offshore South Africa and is largely underexplored. The basin, that hosts two gas field namely the Ibhubesi and the Kudu gas fields, has large potential but in the past has not been given due attention with only 34 wells being drilled in the area. The Orange basin has recently been the topic of investigation because of the belief that it may be hosts to more hydrocarbons. This study will utilise Chemostratigraphy to attempt to provide geological information on this relatively under-explored basin. The aim of this research study is to produce a chemostratigraphic framework -scheme for the Orange Basin in order to facilitate reservoir scale interwell correlation. The Objectives of this research study will be to identify chemostratigraphic units or indices, to prove the adequate use of chemostratigraphy as an independent correlation technique and to integrate the chemostratigraphy and petrophysical characteristics of the four wells to facilitate lithological identification.</p>

Magister Scientiae - MSc / Many hydrocarbon reservoirs are situated in barren sequences that display poor stratigraphic control. Correlation between the wells can become extremely difficult and traditional correlation techniques can prove to be inadequate. Past studies have shown that trace and major element concentrations can be used as a correlation tool. This practice of using geochemical fingerprints to characterize between wells is called Chemostratigraphic analysis. (Pearce et al, 1999) Chemostratigraphy has been recognized as a very important correlation technique as it can be used for rocks of any age, in any geological setting as well as sequences that are traditionally defined as barren. Chemostratigraphic analyses can be used as a means of getting rid of ambiguities within data produced by traditional correlation methods such as Biostratigraphy, Lithostratigraphy and Geophysical Logging. In areas where stratigraphic data is not available it can be used to construct correlation frameworks for the sequences found in the area. The motivation behind this study is that the research is not only worthy of academic investigation, but can also provide the industry with new insights into areas that were previously misunderstood because traditional correlation methods were not adequate. The study area, the Orange basin, is located offshore South Africa and is largely underexplored. The basin, that hosts two gas field namely the Ibhubesi and the Kudu gas fields, has large potential but in the past has not been given due attention with only 34 wells being drilled in the area. The Orange basin has recently been the topic of investigation because of the belief that it may be hosts to more hydrocarbons. This study will utilise Chemostratigraphy to attempt to provide geological information on this relatively under-explored basin. The aim of this research study is to produce a chemostratigraphic framework -scheme for the Orange Basin in order to facilitate reservoir scale interwell correlation. The Objectives of this research study will be to identify chemostratigraphic units or indices, to prove the adequate use of chemostratigraphy as an independent correlation technique and to integrate the chemostratigraphy and petrophysical characteristics of the four wells to facilitate lithological identification. / South Africa

>Magister Scientiae - MSc / Many hydrocarbon reservoirs are situated in barren sequences that display poor stratigraphic control. Correlation between the wells can become extremely difficult and traditional correlation techniques can prove to be inadequate. Past studies have shown that trace and major element concentrations can be used as a correlation tool. This practice of using geochemical fingerprints to characterize between wells is called Chemostratigraphic analysis. (Pearce et al, 1999) Chemostratigraphy has been recognized as a very important correlation technique as it can be used for rocks of any age, in any geological setting as well as sequences that are traditionally defined as barren. Chemostratigraphic analyses can be used as a means of getting rid of ambiguities within data produced by traditional correlation methods such as Biostratigraphy, Lithostratigraphy and Geophysical Logging. In areas where stratigraphic data is not available it can be used to construct correlation frameworks for the sequences found in the area. The motivation behind this study is that the research is not only worthy of academic investigation, but can also provide the industry with new insights into areas that were previously misunderstood because traditional correlation methods were not adequate. The study area, the Orange basin, is located offshore South Africa and is largely underexplored. The basin, that hosts two gas field namely the Ibhubesi and the Kudu gas fields, has large potential but in the past has not been given due attention with only 34 wells being drilled in the area. The Orange basin has recently been the topic of investigation because of the belief that it may be hosts to more hydrocarbons. This study will utilise Chemostratigraphy to attempt to provide geological information on this relatively under-explored basin. The aim of this research study is to produce a chemostratigraphic framework -scheme for the Orange Basin in order to facilitate reservoir scale interwell correlation. The Objectives of this research study will be to identify chemostratigraphic units or indices, to prove the adequate use of chemostratigraphy as an independent correlation technique and to integrate the chemostratigraphy and petrophysical characteristics of the four wells to facilitate lithological identification. Element distribution Analysis was done on the data. This brought to the fore. the dominance of Si02 across the samples for the four wells. Ah03 concentrations were relatively high across the wells and were indicative of the clay rich nature of the samples. This also indicated that the samples were relatively immature. Principal Component Analysis (PCA) plots were constructed for the purpose of identifying diametrical relationships between the elements or element clusters. These diametric relationships were in turn used to calculate the geochemical indices. The relative positions of the elements on the PCA plot highlighted the presence of alternating units of sandstone, feldspathic sandstone, calcareous clays and non calcareous clays within the samples. The PCA plots displayed diametric relationships between Si02 and the carbonate mineral clusters, Si02 and the clay mineral clusters, Nd and V, Nb nad Ni, Zr and Co, Nb and Zn. Si02 and Co, Y and Pb, Zr and Sr, and lastly Nb and Ra / Downhole plots were constructed to illustrate recognizable trends in the PCA plot and to relate this to the occurrence of various lithologies in the wells. Based on the element distribution patterns, PCA plots and Major and Trace element downhole profiles geochemical indices were calculated. They are grouped into three clusters, ratios indicative of the presence of clean sandstones (High Si02/Ah03, Si02/Co, Zr/Co, Zr/Sr, YlPb and low Nd/V values); ratios indicative of the presence of clays (Low Si02/Ah03, Fe203/Ah03, Si02/Co, Zr/Co, YlPb and high Rb/Zn values); thirdly those indicative of the presence of feldspathic sandstones (High Na201K20) and lastly those indicative of the presence of carbonates (low Zr/Sr). Using the geochemical Indices six units were identified in Well A_AI, nine in A-II and 8 iin Well A-UI and A-LI. Four units (A-D) were found to correlate across the wells. I Well log interpretation for the Wells A-AI, A-II, A-Lland A-UI started with a general overview of the log responses. The log responses for the four wells highlighted the presence of sandstones, argillaceous sandstones, shales and shale components. Geophysical units were identified using the logs responses. Six units were identified in Well A-AI, nine in Well A-II and eight in Wells A-LI and A-UI. These units coincide with the units identified using Chemostratigraphic analysis. Neutron - Density cross plots were constructed for each unit across the four wells. The plotting of the points on the Neutron - Density cross plots for the wells A-AI, A-II, A-LI and A-UI indicated the presence of sandstones, shales or greywackes and either limestones and dolomites but from the geochemistry it is known that neither limestone nor dolomite is present in the wells and it was thus inferred that the points plotting between the limestone and dolomite lithology curves indicated the presence of calcareous shales. M-N plots were constructed for each unit. The patterns exhibited by the points on the M-N plots for the wells was indicative of the presence calcareous clays, sandstones, greywacke and shales. The Chemostratigraphic and Petrophysical results produced accurate and comparable results, however, the Chemostratigraphic analysis provided finer details regarding the lithology of the units. Based on the well log responses no distinction could be made between highly feldspathic sandstone, arkosic and argillaceous sandstone, while these distinctions were possible when analyzing the samples using Chemostratigraphy. The geochemistry was capable of providing signatures in areas where the wireline tools malfunctioned. The logs, on the other hand, sheds light on properties such as porosity and permeability of the rocks which cannot be obtained accurately from the geochemistry. When comparing the correlation capabilities of these two techniques, the one based on geochemical signatures and the other based on the responses obtained from wireline tools, it is important to acknowledge that both these techniques has strengths and weaknesses. The best of both these techniques can only be fully utilised when either technique is used in conjunction with other techniques. With respect to the Orange Basin, located offshore South Africa, it can be concluded that the dominant lithologies in the basin are sandstones, argillaceous sandstones, shales, feldspathic and arkosic sandstones and clays. In terms of petroleum prospectivity the sandstones in Wells A-AI, A-II, A-UI and A-LI could possibly be considered to be reservoirs and the shales could be considered to be seals or source rocks, depending on the organic matter content. On the down side, the sandstones display relatively poor permeabilities and the porosities are variable. The density logs indicate that the sandstones are highly compacted and that could be an indication of poor porosities but more research needs to be done. Another factor highlighted from the research is the presence of alternating lithologies. This means that the reservoirs are compartmentalised and that the area has a high degree of heterogeneity.