This research combines a statistical tool called experimental design/response surface methodology with reservoir modeling and flow simulation for the purpose of reservoir characterization. Very often, it requires large number of reservoir simulation runs for identifying significant reservoir modeling parameters impacting flow response and for history matching. Experimental design/response surface (ED/RS) is a statistical technique, which allows a systematic approach for minimizing the number of simulation runs to meet the two objectives mentioned above. This methodology may be applied to synthetic and field cases using existing statistical software tools. The application of ED/RS methodology for the purpose of reservoir characterization has been applied for two different objectives. The first objective is to address the uncertainties in the identification of the location and transmissibility of flow barriers in a field in the Gulf of Mexico. This objective is achieved by setting up a simple full-factorial design. The range of transmissibility of the barriers is selected using a Latin Hypercube Sampling (LHS). An analysis of variance (ANOVA) gives the significance of the location and transmissibility of barriers and comparison with decline-type curve analysis which gives us the most likely scenarios of the location and transmissibility of the flow barriers. The second objective is to identify significant geologic parameters in object-based and pixel-based reservoir models. This study is applied on a synthetic fluvial reservoir, whose characteristic feature is the presence of sinuous sand filled channels within a background of floodplain shale. This particular study reveals the impact of uncertainty in the reservoir modeling parameters on the flow performance. Box-Behnken design is used in this study to reduce the number of simulation runs along with streamline simulation for flow modeling purposes. In the first study, we find a good match between field data and that predicted from streamline simulation based on the most likely scenario. This validates the use of ED to get the most likely scenario for the location and transmissibility of flow barriers. It can be concluded from the second study that ED/RS methodology is a powerful tool along with a fast streamline simulator to screen large number of reservoir model realizations for the purpose of studying the effect of uncertainty of geologic modeling parameters on reservoir flow behavior.

The Rodessa Formation is one of the major oil and gas reservoirs in the East Texas Basin. In Van Field, the upper Rodessa Formation consists of interbedded biotic and abiotic mudstones to grainstones. The lower Rodessa is composed of interbedded sandstones, shales, and limestones called the Carlisle Member. Based on core and well log interpretation, the Rodessa Formation was deposited on a broad, restricted, shallow marine platform interpreted to be lagoonal, subtidal, and intertidal. Both Rodessa limestone and sandstone have been altered significantly by diagenetic processes that include micritization, cementation, dissolution, neomorphism and compaction. Dissolution is the main factor that resulted in enhanced porosity and permeability while cementation adversely affected porosity. Diagenesis is interpreted to have begun in the marine phreatic environment and continued through the freshwater phreatic and shallow burial environments. Two reservoir units have been identified from core and well log interpretations. The potential reservoir within the Rodessa Formation occurs in the Carlisle Member which is composed mainly of medium to coarse grained sandstone with porosities and permeabilities in ranges of 8 to 11 percent and 46 to 896 millidarcies, respectively. The water saturation analysis has also shown the reservoir to be hydrocarbon bearing, having water saturation below 46 percent.

The Spraberry Formation is traditionally thought of as deep-water turbidites in the central Midland Basin. At Happy Spraberry field, Garza County, Texas, however, production is from a carbonate interval about 100 feet thick that has been correlated on seismic sections with the Leonardian aged, Lower Clear Fork Formation. The "Happy field" carbonates were deposited on the Eastern Shelf of the Midland Basin and consist of oolitic skeletal grainstones and packstones, rudstones and floatstones, in situ Tubiphytes bindstones, and laminated to rippled, very-fine grained siltstones and sandstones. The highest reservoir "quality" facies are in the oolitic grainstones and packstones where grain-moldic and solution-enhanced intergranular porosity dominate. Other pore types present include incomplete grain moldic, vuggy, and solution-enhanced intramatrix. The purpose of this study was to relate pore geometry measured by digital petrographic image analysis to petrophysical characteristics, and finally, to reservoir quality. Image analysis was utilized to obtain size, shape, frequency, and total abundance of pore categories. Pore geometry and percent porosity were obtained by capturing digital images from thin sections viewed under a petrographic microscope. The images were transferred to computer storage for processing with a commercial image analysis program trademarked as Image Pro Plus (Version 4.0). A classification scheme was derived from the image processing enabling "pore facies" to be established. Pore facies were then compared to measured porosity and permeability from core analyses to determine relative "quality" of reservoir zones with different pore facies. Pore facies are defined on pore types, sizes, shapes, and abundances that occur in reproducible associations or patterns. These patterns were compared with porosity and permeability values from core analyses. Four pore facies were identified in the Happy field carbonates; they were examined for evidence of diagenetic change, depositional signatures, and fractures. Once the genetic categories were established for the four pore facies, the pore groups could be reexamined in stratigraphic context and placed in the stratigraphic section across Happy field. Finally, the combined porosity and permeability values characteristic of each pore facies were used to identify and rank good, intermediate, and poor flow units at field scale.

Seismic time-lapse monitoring of production is an important tool used to efficiently drain a hydrocarbon reservoir. Repeat seismic surveys may be used, because the seismic method is sensitive to the reservoir fluid. A prominent seismic attribute is the reflectivity (or amplitude) as a function of offset (AVO) which strongly depends on material properties, and hence, on the pore fluid. Repeat surveys, however, are very costly. To reduce the risks, the repeat survey is simulated on a computer for a number of different scenarios. Hence, the objectives of this study are to predict the seismic responses after five years of production of the reservoirs at the well locations, correlate the seismic attributes to fluid conditions in the reservoirs, assess the detectability of changes in AVO attributes due to changes in fluid conditions, and determine which attribute is more diagnostic of fluid changes. Petrophysical models were generated for different pore fluids using well logs from a field in the Gulf of Mexico. Synthetic seismograms were then calculated using a layerstack scheme to study the effects of the reservoir fluids on AVO. Compared to idealized half-space models, it was found that the AVO responses are contaminated by the overburden and the thinness of the reservoir. In order to remove transmission loss due to overburden effects, the synthetic AVO curves were scaled by normalizing an overburden-over-half-space model to an idealized analytical Zoeppritz model. In a second step, an offset-dependent overburden correction was applied using a low order polynomial, which was fitted to the amplitude ratios between the overburden/half-space model and the idealized model. Finally, a zero-offset tuning correction was applied. The results of the AVO analyses showed that some errors were unresolved using the applied overburden and tuning corrections, and amplitudes at large offsets were possibly contaminated by multiples and converted waves. Since there is no shallower production or steam injection for this particular field, the repeat surveys should have the same overburden, tuning, multiple-related and converted wave contamination. It appears reasonable to assume that any changes in amplitude between the repeat surveys would be due to fluid saturation changes. Therefore, it was concluded that it is not necessary to attempt to remove the overburden and tuning effects. Results from the AVO analyses of the uncorrected models showed that AVO attributes should be a useful tool to detect reservoir conditions during the production of the field. Generally, the water-flood changes the AVO by decreasing the intercept and increasing the gradient from the in-situ oil/gas cases. The relative changes in both intercept and gradient due to the water-flood are detectable assuming a 20% relative-change detection threshold, and gradient is more diagnostic because the relative change in gradient is very large compared to that for intercept. / Master of Science

A detailed laboratory study of sandstone samples from outcrops and conventional core samples from the Maastrichtian-Paleocene Scollard-age fluvial strata in the Western Canada foredeep was undertaken to investigate the reservoir characteristics, burial depth history, and sandstone diagenesis. The sandstones are predominantly litharenites and sublitharenites, which accumulated in a variety of fluvial environments. The porosity of the sandstones is both syn-depositional and diagenetic in origin. The potential of a sandstone to serve as a reservoir for producible hydrocarbons is strongly related to the sandstones diagenetic history. Detailed study of the distribution of authigenic minerals of the Scollard sequence suggests that the diversities in the pattern distribution of authigenic clay minerals in the regions are not random but they coincide with the burial depth of these strata and has a well-defined relation to the sequence stratigraphic framework The general absence of dickite, coupled with limited conversion of smectite into illite in the Scollard sandstones, suggests crystallization at a depth less than 1.5 km. In contrast, the occurrence of blocky dickite, fibrous illite and chlorite in the Coalspur and Willow Creek sandstones, coupled with albitized feldspars and quartz cement, suggests that sandstones there underwent a maximum burial depth greater than 3 km. It has been observed that kaolin mineral content increases in sandstones lying below subaerial unconformities, which mark the most significant stratigraphic hiatuses and hence the sequence boundaries in fully fluvial successions. This study demonstrates the effects of burial depth and paleoclimate on pore-water chemistry, which in turn, influenced the mineralogy and the distributions of authigenic minerals in the sandstones. The 13C and 18O compositions of pedogenic carbonate nodules from the Willow Creek Formation associated with the red shale host sediments have been used as a paleoclimate and paleoenvironmental proxy. The isotopic composition of nodules suggests that these formed during drier conditions when C3 vegetation prevailed at the site. The predominance of smectite and illite in fines and the poor floral content point to a low seasonal rainfall in a semi-arid climatic environment.

No description available.

Turbidite reservoirs in deep-water depositional systems, such as the oil fields in the offshore Gulf of Mexico and North Sea, are becoming an important exploration target in the petroleum industry. Accurate seismic reservoir characterization, however, is complicated by the heterogeneous of the sand and shale distribution and also by the lack of resolution when imaging thin channel deposits. Amplitude variation with offset (AVO) is a very important technique that is widely applied to locate hydrocarbons. Inaccurate estimates of seismic reflection amplitudes may result in misleading interpretations because of these problems in application to turbidite reservoirs. Therefore, an efficient, accurate, and robust method of modeling seismic responses for such complex reservoirs is crucial and necessary to reduce exploration risk. A fast and accurate approach generating synthetic seismograms for such reservoir models combines wavefront construction ray tracing with composite reflection coefficients in a hybrid modeling algorithm. The wavefront construction approach is a modern, fast implementation of ray tracing that I have extended to model quasishear wave propagation in anisotropic media. Composite reflection coefficients, which are computed using propagator matrix methods, provide the exact seismic reflection amplitude for a stratified reservoir model. This is a distinct improvement over conventional AVO analysis based on a model with only two homogeneous half spaces. I combine the two methods to compute synthetic seismograms for test models of turbidite reservoirs in the Ursa field, Gulf of Mexico, validating the new results against exact calculations using the discrete wavenumber method. The new method, however, can also be used to generate synthetic seismograms for the laterally heterogeneous, complex stratified reservoir models. The results show important frequency dependence that may be useful for exploration. Because turbidite channel systems often display complex vertical and lateral heterogeneity that is difficult to measure directly, stochastic modeling is often used to predict the range of possible seismic responses. Though binary models containing mixtures of sands and shales have been proposed in previous work, log measurements show that these are not good representations of real seismic properties. Therefore, I develop a new approach for generating stochastic turbidite models (STM) from a combination of geological interpretation and well log measurements that are more realistic. Calculations of the composite reflection coefficient and synthetic seismograms predict direct hydrocarbon indicators associated with such turbidite sequences. The STMs provide important insights to predict the seismic responses for the complexity of turbidite reservoirs. Results of AVO responses predict the presence of gas saturation in the sand beds. For example, as the source frequency increases, the uncertainty in AVO responses for brine and gas sands predict the possibility of false interpretation in AVO analysis.

Reservoir models are generally constructed from seismic, well logs and other related datasets using inversion methods and geostatistics. It has already been recognized by the geoscientists that such a process is prone to non-uniqueness. Practical methods for estimation of uncertainty still remain elusive. In my dissertation, I propose two new methods to estimate uncertainty in reservoir models from seismic, well logs and well production data. The first part of my research is aimed at estimating reservoir impedance models and their uncertainties from seismic data and well logs. This constitutes an inverse problem, and we recognize that multiple models can fit the measurements. A deterministic inversion based on minimization of the error between the observation and forward modeling only provides one of the best-fit models, which is usually band-limited. A complete solution should include both models and their uncertainties, which requires drawing samples from the posterior distribution. A global optimization method called very fast simulated annealing (VFSA) is commonly used to approximate posterior distribution with fast convergence. Here I address some of the limitations of VFSA by developing a new stochastic inference method, named Greedy Annealed Importance Sampling (GAIS). GAIS combines VFSA with greedy importance sampling (GIS), which uses a greedy search in the important regions located by VFSA to attain fast convergence and provide unbiased estimation. I demonstrate the performance of GAIS on post- and pre-stack data from real fields to estimate impedance models. The results indicate that GAIS can estimate both the expectation value and the uncertainties more accurately than using VFSA alone. Furthermore, principal component analysis (PCA) as an efficient parameterization method is employed together with GAIS to improve lateral continuity by simultaneous inversion of all traces. The second part of my research involves estimation of reservoir permeability models and their uncertainties using quantitative joint inversion of dynamic measurements, including synthetic production data and time-lapse seismic related data. Impacts from different objective functions or different data sets on the model uncertainty and model predictability are investigated as well. The results demonstrate that joint inversion of production data and time-lapse seismic related data (water saturation maps here) reduces model uncertainty, improves model predictability and shows superior performance than inversion using one type of data alone. / text

This dissertation focuses on interpreting the spatial variations of seismic amplitude data as a function of rock properties for the Haynesville Shale. To achieve this goal, I investigate the relationships between the rock properties and elastic properties, and calibrate rock-physics models by constraining both P- and S-wave velocities from well log data. I build a workflow to estimate the rock properties along with uncertainties from the P- and S-wave information. I correlate the estimated rock properties with the seismic amplitude data quantitatively. The rock properties, such as porosity, pore shape and composition, provide very useful information in determining locations with relatively high porosities and large fractions of brittle components favorable for hydraulic fracturing. Here the brittle components will have the fractures remain opened for longer time than the other components. Porosity helps to determine gas capacity and the estimated ultimate recovery (EUR); composition contributes to understand the brittle/ductile strength of shales, and pore shape provides additional information to determine the brittle/ductile strength of the shale. I use effective medium models to constrain P- and S-wave information. The rock-physics model includes an isotropic and an anisotropic effective medium model. The isotropic effective medium model provides a porous rock matrix with multiple mineral phases and pores with different aspect ratios. The anisotropic effective medium model provides frequency- and pore-pressure-dependent anisotropy. I estimate the rock properties with uncertainties using grid searching, conditioned by the calibrated rock-physics models. At well locations, I use the sonic log as input in the rock-physics models. At areas away from the well locations, I use the prestack seismic inverted P- and S-impedances as input in the rock-physics models. The estimated rock properties are correlated with the seismic amplitude data and help to interpret the spatial variations observed from seismic data. I check the accuracy of the estimated rock properties by comparing the elastic properties from seismic inversion and the ones derived from estimated rock properties. Furthermore, I link the estimated rock properties to the microstructure images and interpret the modeling results using observations from microstructure images. The characterization contributes to understand what causes the seismic amplitude variations for the Haynesville Shale. The same seismic reservoir characterization procedure could be applied to other unconventional gas shales. / text

Microbial actions on coal have long been identified as a source of methane in coalbeds. Andrew Scott (1995) was the first to propose imitating the natural process of biogenic gasification, possibly leading to recharging coalbed methane (CBM) reservoirs, or setting up natural gas reservoirs in non-producing coalbeds. This study was aimed at identifying the changes in coal properties that affect gas deliverability in coal-gas reservoirs, when treated with microbial consortia to generate/enhance gas production. The experimental work tested the sorption and diffusion properties for the coal treated and, more importantly, the variation in the relevant parameters with continued bio-conversion since these are the first two phenomena in CBM production. During the first phase, single component sorption-diffusion experiments were carried out using pure methane and CO2 on virgin/baseline coals, retrieved from the Illinois basin. Coals were then treated with nutrient amended microbial consortia for different periods. Gas production was monitored at the end of thirty and sixty days of treatment, after which, sorption-diffusion experiments were repeated on treated coals, thus establishing a trend over the sixty-day period. The sorption data was characterized using Langmuir pressure and volume constants, obtained by fitting it over the Langmuir isotherm. The diffusion coefficient, D, was estimated by establishing the variation trend as a function of pore pressure. The pressure parameter was considered critical since, with continued production of methane, the produced gas diffuses into the coal matrix, where it gets adsorbed with increasing pressure. During production, the pressure decreases and the process is reversed, gas diffusing out of the coal matrix and arriving at the cleat system. The results indicated an increase in the sorption capacity of coal as a result of bioconversion. This was attributed to increased pore surface areas as a result of microbial actions. However, significant hysteresis was observed during desorption of methane and was attributed to preferential desorption from sorption sites in the pathways leading to pore cavities. This is corroborated by the increased rates of diffusion, especially for methane, which exhibited rates higher than that for CO2. This contradicted the results for untreated/baseline coal, which were in agreement with previous studies. Effort was made to explain this anomaly by the non-monotonic dependence of effective diffusion coefficient on the size of the diffusing particles, where in coalbed environments, CO2 has smaller kinetic diameter than methane.