The ever increasing energy demand brings about widespread interest to rapidly, profitably and efficiently develop unconventional resources, among which tight gas sands hold a significant portion. However, optimization of development strategies in tight gas fields is challenging, not only because of the wide range of depositional environments and large variability in reservoir properties, but also because the evaluation often has to deal with a multitude of wells, limited reservoir information, and time and budget constraints. Unfortunately, classical full-scale reservoir evaluation cannot be routinely employed by small- to medium-sized operators, given its timeconsuming and expensive nature. In addition, the full-scale evaluation is generally built on deterministic principles and produces a single realization of the reservoir, despite the significant uncertainty faced by operators. This work addresses the need for rapid and cost-efficient technologies to help operators determine optimal well spacing in highly uncertain and risky unconventional gas reservoirs. To achieve the research objectives, an integrated reservoir and decision modeling tool that fully incorporates uncertainty was developed. Monte Carlo simulation was used with a fast, approximate reservoir simulation model to match and predict production performance in unconventional gas reservoirs. Simulation results were then fit with decline curves to enable direct integration of the reservoir model into a Bayesian decision model. These integrated tools were applied to the tight gas assets of Unconventional Gas Resources Inc. in the Berland River area, Alberta, Canada.

The purpose of the research is to study the solutions for the difficulties encountered in the water resources development in southern Taiwan. In the recent years, Owing to the phenomenon of global warming, many countries in the world experienced more powerful flood and longer drought then before. The water resources development of southern Taiwan is very difficult not only because the limitation of the weather and geographical condition, but also the hinder of the inner and outside factors of government organizations. The inner factors majorly include : The opinions of central government and local government cannot be integrated effectively like the old province government and results in the suspension of the engineering land acquisition. The authority¡¦s policy of water resource development is unstable, which also make the situation worse. The outside factors majorly includes: The intention of the local government authority can be affected easily by the effect of NIMBY and the pressure of environmental protection group,which causes the problem of land acquisition becoming more complicated and harder to resolve. This paper trys to study the cases of Ma-Tan Reservoir and Tseng-Wen Reservoir Transbasin Water diversion project, based on the efficiency of the land acquisition of the province government, to analyse the inner and outside factors and the dealing mechanism of government to provide some suggestions for the government.

Siltation in reservoirs is becoming an important problem as the dams are getting older in the world. The general dam practice has been implemented in a sequence that / planning, design, construction, operation of dam until the accumulated sediment prevents its purpose function or functions. Unfortunately, effects of sedimentation and fate of the left over dams in the future are not figured. Indeed, these negative effects could be avoided, life of the reservoir can be prolonged and even the reservoir will last forever by minimizing the sedimentation. Therefore in this study, the methods that provide extension of reservoir life are discussed hydraulically, economically and applicability point of view. In addition, there is open source package program RESCON which examines and compares some sediment removal techniques economically and also hydraulically. RESCON is used in conjunction with several cases / namely &Ccedil / ubuk Dam-I, Bor&ccedil / ka Dam and Muratli Dam. Moreover, some sensitivity analyses are carried out in order to scrutiny of the program for Turkish economic conditions.

Reconciling high-resolution geologic models to field production history is still a very time-consuming procedure. Recently streamline-based assisted and automatic history matching techniques, especially production data integration by “travel-time matching,” have shown great potential in this regard. But no systematic study was done to examine the merits of travel-time matching compared to more traditional amplitude matching for field-scale application. Besides, most applications were limited to two-phase water-oil flow because current streamline models are limited in their ability to incorporate highly compressible flow in a rigorous and computationally efficient manner. The purpose of this work is fourfold. First, we quantitatively investigated the nonlinearities in the inverse problems related to travel time, generalized travel time, and amplitude matching during production data integration and their impact on the solution and its convergence. Results show that the commonly used amplitude inversion can be orders of magnitude more nonlinear compared to the travel-time inversion. Both the travel-time and generalized travel time inversion (GTTI) are shown to be more robust and exhibit superior convergence characteristics. Second, the streamline-based assisted history matching was enhanced in two important aspects that significantly improve its efficiency and effectiveness. We utilize streamline-derived analytic sensitivities to determine the location and magnitude of the changes to improve the history match, and we use the iterative GTTI for model updating. Our approach leads to significant savings in time and manpower. Third, a novel approach to history matching finite-difference models that combines the efficiency of analytical sensitivity computation of the streamline models with the versatility of finite-difference simulation was developed. Use of finite-difference simulation can account for complex physics. Finally, we developed an approach to history matching three-phase flow using a novel compressible streamline formulation and streamline-derived analytic sensitivities. Streamline models were generalized to account for compressible flow by introducing a relative density of total fluids along streamlines and a density-dependent source term in the saturation equation. The analytical sensitivities are calculated based on the rigorous streamline formulation. The power and utility of our approaches have been demonstrated using both synthetic and field examples.

The demand for oil and gas is increasing yearly, whereas proven oil and gas reserves are being depleted. The potential of stripper oil and gas fields to supplement the national energy supply is large. In 2006, stripper wells accounted for 15% and 8% of US oil and gas production, respectively. With increasing energy demand and current high oil and gas prices, integrated reservoir studies, secondary and tertiary recovery methods, and infill drilling are becoming more common as operators strive to increase recovery from stripper oil and gas fields. The primary objective of this research was to support optimized production of oil and gas from stripper well fields by evaluating one stripper gas field and one stripper oil field. For the stripper gas field, I integrated geologic and engineering data to build a detailed reservoir characterization model of the Second White Specks (SSPK) reservoir in Garden Plains field, Alberta, Canada. The objectives of this model were to provide insights to controls on gas production and to validate a simulation-based method of infill drilling assessment. SSPK was subdivided into Units A ? D using well-log facies. Units A and B are the main producing units. Unit A has better reservoir quality and lateral continuity than Unit B. Gas production is related primarily to porosity-netthickness product and permeability and secondarily to structural position, minor structural features, and initial reservoir pressure. For the stripper oil field, I evaluated the Green River formation in the Wells Draw area of Monument Butte field, Utah, to determine interwell connectivity and to assess optimal recovery strategies. A 3D geostatistical model was built, and geological realizations were ranked using production history matching with streamline simulation. Interwell connectivity was demonstrated for only major sands and it increases as well spacing decreases. Overall connectivity is low for the 22 reservoir zones in the study area. A water-flood-only strategy provides more oil recovery than a primary-then-waterflood strategy over the life of the field. For new development areas, water flooding or converting producers to injectors should start within 6 months of initial production. Infill drilling may effectively produce unswept oil and double oil recovery. CO2 injection is much more efficient than N2 and CH4 injection. Water-alternating-CO2 injection is superior to continuous CO2 injection in oil recovery. The results of this study can be used to optimize production from Garden Plains and Monument Butte fields. Moreover, these results should be applicable to similar stripper gas and oil field fields. Together, the two studies demonstrate the utility of integrated reservoir studies (from geology to engineering) for improving oil and gas recovery.

While geophysical reservoir characterization has been an area of research for the last three decades, geophysical reservoir monitoring, time-lapse studies, have recently become an important geophysical application. Generally speaking, the main target is to detect, estimate, and discriminate the changes in subsurface rock properties due to production. This research develops various sensitivity and feasibility analyses to investigate the effects of production-induced time-lapse changes on geophysical measurements including seismic and controlled-source electromagnetic (CSEM) data. For doing so, a realistic reservoir model is numerically simulated based on a prograding near-shore sandstone reservoir. To account for the spatial distribution of petrophysical properties, an effective porosity model is first simulated by Gaussian geostatistics. Dispersed clay and dual water models are then efficiently combined with other well-known theoretical and experimental petrophysical correlations to consistently simulate reservoir model parameters. Next, the constructed reservoir model is subjected to numerical simulation of multi-phase fluid flow to replicate a waterflooding scenario of a black oil reservoir and to predict the spatial distributions of fluid pressure and saturation. A modified Archie’s equation for shaly sandstones is utilized to simulate rock resistivity. Finally, a geologically consistent stress-sensitive rock physics model, combined with the modified Gassmann theory for shaly sandstones, is utilized to simulate seismic elastic parameters. As a result, the comprehensive petro-electro-elastic model developed in this dissertation can be efficiently utilized in sensitivity and feasibility analyses of seismic/CSEM data with respect to petrophysical properties and, ultimately, applied to reservoir characterization and monitoring research. Using the resistivity models, a base and two monitor time-lapse CSEM surveys are simulated via accurate numerical algorithms. 2.5D CSEM modeling demonstrates that a detectable time-lapse signal after 5 years and a strong time-lapse signal after 10 years of waterflooding are attainable with the careful application of currently available CSEM technology. To simulate seismic waves, I employ different seismic modeling algorithms, one-dimensional (1D) acoustic and elastic ray tracing, 1D full elastic reflectivity, 2D split-step Fourier plane-wave (SFPW), and 2D stagger grid explicit finite difference (FD). My analyses demonstrate that acoustic modeling of an elastic medium is a good approximation up to ray parameter (p) equal to 0.2 sec/km. However, at p=0.3 sec/km, differences between elastic and acoustic wave propagation is the more dominant effect compared to internal multiples. Here, converted waves are also generated with significant amplitudes compared to primaries and internal multiples. I also show that time-lapse modeling of the reservoir using SFPW approach is very fast compared to FD, 100 times faster for my case here. It is capable of handling higher frequencies than FD. It provides an accurate image of the waterflooding process comparable to FD. Consequently, it is a powerful alternative for time-lapse seismic modeling. I conclude that both seismic and CSEM data have adequate but different sensitivities to changes in reservoir properties and therefore have the potential to quantitatively map production-induced time-lapse changes. / text

The performance of Enhanced Oil Recovery (EOR) processes is adversely affected by the heterogeneous distribution of flow properties of the rock. The effects of heterogeneity are further highlighted when the mobility ratio between the displacing and the displaced fluids is unfavorable. Polymer flooding aims to mitigate this by controlling the mobility ratio resulting in an increase in the volumetric swept efficiency. However, the design of the polymer injection process has to take into account the uncertainty due to a limited knowledge of the heterogeneous properties of the reservoir. Numerical reservoir models equipped with the most updated, yet uncertain information about the reservoir should be employed to optimize the operational settings. Consequently, the optimal settings are uncertain and should be revised as the model is updated. In this report, a feedback-control scheme is proposed with a model updating step that conditions prior reservoir models to newly obtained dynamic data, and this followed by an optimization step that adjusts well control settings to maximize (or minimize) an objective function. An illustration of the implementation of the proposed closed-loop scheme is presented through an example where the rate settings of a well affected by water coning are adjusted as the reservoir models are updated. The revised control settings yield an increase in the final value of the objective function. Finally, a fast analog of a polymer flooding displacement that traces the movement of random particles from injectors to producers following probability rules that reflect the physics of the actual displacement is presented. The algorithm was calibrated against the full-physics simulation results from UTCHEM, the compositional chemical flow simulator developed at The University of Texas at Austin. This algorithm can be used for a rapid estimation of basic responses such as breakthrough time or recovery factor and to provide a simplified characterization the reservoir heterogeneity. This report is presented to fulfill the requirements to obtain the degree of Master of Science in Engineering under fast track option. It summarizes the research proposal presented for my doctorate studies that are currently ongoing. / text

The Late Jurassic Arab D Formation in Saudi Arabia hosts the some of the world’s largest hydrocarbon reservoirs including Ghawar, the world’s largest oil field, and Khurais, the world’s largest supergiant to come into production in the last 5 years. Despite the vast oil reserves within the Arab D, and the central role of this reservoir at Ghawar in making up short-falls in global production, our understanding of the much fundamental characterization work both in terms of modern sequence stratigraphic reservoir frameworks and linked structural/fracture characterization. This study of Arab D reservoir at Qatif, immediately to the north of Ghawar, provides one of the first looks at a modern sequence analysis of this producing interval and illustrates that porosity zonations, and ultimately flow unit architecture may be substantially different than currently in use. The Arab D of the Arabian Plate is a carbonate ramp system of exceedingly low angle (<1o) developed during a low-eustatic-amplitude greenhouse Milankovitch setting. Combined macroscopic and petrographic data analysis allowed recognition of nine depositional facies: 1) spiculitic wackestone, 2) Planolites-burrowed wackestone, 3) bioturbated skeletal-peloidal packstone, 4) pelletal packstone, 5) peloidal-skeletal grain dominated packstone, 6) peloidal-skeletal grainstone, 7) skeletal-ooids grainstone, 8) cryptalgal laminites and 9) anhydrite. The depositional facies defined are used to interpret three facies tracts from deep to shallow across the ramp profile: 1) low energy sub-storm wave base (SWB) dominated facies that may illustrate disaerobic tendencies, 2) high energy within-fair-weather-wave-base ramp-crest or mid-ramp facies including foreshore and upper shoreface oolitic and skeletal grainstones that define one of the key reservoir pay zones and 3) back-barrier tidal flats consisting of cryptalgal laminites, sabkha-type anhydrites, and salina-type anhydrites. Three high frequency sequences are defined: QSEQ 1 is asymmetrical, dominated by subtidal lithofacies; and QSEQ 2 and QSEQ 3 are symmetrical and record a complex history of the fill on an intrashelf basin. Detailed cycle-scale correlations using core-based cycles and wireline log patterns allowed a cycle-scale correlation framework to be established that illustrates a north to south progradation of the Arab D reservoir strata, building landward from the Rimthan Arch. Diagenetic features observed in the Arab D reservoir include fitted fabric (chemical compaction), dolomitization, and cementation. These features play a major role altering reservoir quality properties as they essentially control fluid flow pathways which ultimately alter primary porosity and permeability. / text

Reservoir souring refers to the increase in the concentration of hydrogen sulfide in production fluids during waterflooding. Besides health and safety issues, H₂S content reduces the value of the produced hydrocarbon. Nitrate injection is an effective method to prevent the formation of H₂S. Although the effectiveness of nitrate injection has been proven in laboratory and field applications and biology is well-understood, modeling aspect is still in its early stages. This work describes the modeling and simulation of biological reactions associated with reservoir souring and nitrate injection for souring remediation. The model is implemented in a general purpose adaptive reservoir simulator (GPAS). We also developed a physical dispersion model in GPAS to study the effect of dispersion on reservoir souring. The basic mechanism in the biologically mediated generation of H₂S is the reaction between sulfate and organic compounds in the presence of sulfate-reducing bacteria (SRB). Several mechanisms describe the effect of nitrate injection on reservoir souring. We developed mathematical models for biological reactions to simulate each mechanism. For every biological reaction, we solve a set of ordinary differential equations along with differential equations for the transport of chemical and biological species. Souring reactions occur in the areas of the reservoir where all of the required chemical and biological species are available. Therefore, dispersion affects the extent of reservoir souring as transport of aqueous phase components and the formation of mixing zones depends on dispersive characteristics of porous media. We successfully simulated laboratory experiments in batch reactors and sand-packed column reactors to verify our model development. The results from simulation of laboratory experiments are used to find the input parameters for field-scale simulations. We also examined the effect of dispersion on reservoir souring for different compositions of injection and formation water. Dispersion effects are significant when injection water does not contain sufficient organic compounds and reactions occur in the mixing zone between injection water and formation water. With a comprehensive biological model and robust and accurate flow simulation capabilities, GPAS can predict the onset of reservoir souring and the effectiveness of nitrate injection and facilitate the design of the process. / text

With burgeoning world demand and a limited rate of discovery of new reserves, there is increasing impetus upon the industry to optimize recovery from already existing fields. 4D, or time-lapse, seismic imaging is an emerging technology that holds great promise to better monitor and optimise reservoir production. The basic idea behind 4D seismic is that when multiple 3D surveys are acquired at separate calendar times over a producing field, the reservoir geology will not change from survey to survey but the state of the reservoir fluids will change. Thus, taking the difference between two 3D surveys should remove the static geologic contribution to the data and isolate the timevarying fluid flow component. However, a major challenge in 4D seismic is that acquisition and processing differences between 3D surveys often overshadow the changes caused by fluid flow. This problem is compounded when 4D effects are sought to be derived from vintage 3D data sets that were not originally acquired with 4D in mind. The goal of this study is to remove the acquisition and imaging artefacts from a 4D seismic difference cube using Curvelet processing techniques.