Model Of Reservoir System Research Articles

Evaluating the efficacy of water alternating gas injection technique in the upper jurassic hydrocarbon reservoirs, considering saturation pressure

A tertiary method of enhanced oil recovery (EOR) based on the watergas alternating injection process (WG) is examined in this article based on the ratio between saturation pressure and reservoir pressure. A hydrodynamic simulation of the WAG process was carried out using TEMPEST MORE software (version 7,1). Many hydrocarbon fields worldwide are currently experiencing declining production rates. However, by utilizing advanced technologies like alternate injection of water and associated petroleum gas, the final oil recovery factor (RF) can be significantly increased. To ensure successful water injection experiments in real fields, it is crucial to consider the ratio of saturation and reservoir pressures during injection. Any negligence in this regard can lead to failure of the experiments aimed at enhancing oil recovery through WAG application. The research examines two variations of reservoir system models with certainty. In the initial model, the saturation pressure is lower than the reservoir pressure, signifying an under-saturated state of the reservoir system containing dissolved gas. Consequently, when accompanying petroleum gas is introduced, it mixes with oil at precise thermobaric conditions. According to the second model, the reservoir is saturated with gas at a saturation pressure equivalent to the formation pressure. A thorough assessment indicates that the success of water alternating gas injection (WAG) is heavily influenced by the initial state of the reservoir. In situations where the reservoir is already saturated with gas, implementing water-gas stimulation may be ineffective as gas breakthroughs may occur rapidly. However, implementing WAG in saturated reservoirs can lead to a 1 – 8% rise in overall oil production, observable within 3 – 4 years, depending on the timing after waterflooding. Simultaneously, in the case of reservoirs with a low saturation pressure, which exhibits an undersaturated reservoir system, the implementation of water alternating gas injection can be seen as a viable approach for enhancing oil recovery. WAG is a proven method that confidently increases oil recovery up to 10% in undersaturated reservoirs compared to conventional waterflooding.

Research into phase transformations in reservoir systems models in the presence of thermodynamic hydrate formation inhibitors of high concentration

Gas hydrates have been and still remain a difficult problem in the oil and gas industry, solution of which requires considerable efforts and resources. In this work, the mechanism of phase transformations at negative temperatures in the formation of the solid phase is preliminarily studied using the reservoir system models consisting of a gas mixture and a solution of gas hydrate formation inhibitor of thermodynamic action with high concentration in distilled water. A system of three-dimensional lighting and image magnification is used to visually detect phase boundaries by creating optical effects. Thus, in the system “inhibitor solution – gas hydrate – gas” in the process of gas hydrate recrystallization in the conditions close to equilibrium, microzones of supercooled water may occur, which in the absence of gas molecules access is crystallized into ice. The result of such solid phase structure formation is its increased stability in nonequilibrium conditions for a relatively long period of time.

Forecast-informed reservoir operations to guide hydropower and agriculture allocations in the Blue Nile basin, Ethiopia

ABSTRACT Predictive hydroclimate information, coupled with reservoir system models, offers the potential to mitigate climate variability risks. Prior methodologies rely on sub-seasonal, dynamic/synthetic forecasts at short timescales, which challenge application in practice. Here, coupling a local-scale seasonal, statistical streamflow forecast with a reservoir model addresses this gap, to explore hydropower and agricultural production benefits under various operational strategies. Forecast-informed optimization of reservoir releases increases energy production (6–14%), agriculture allocations (54–68%), and net profit. Application to Ethiopia showcases a novel seasonal-scale statistical forecast coupled reservoir model that translates hydroclimatic predictions into actionable information for better management at the local scale.

Lunar polar water resource exploration – Examination of the lunar cold trap reservoir system model and introduction of play-based exploration (PBE) techniques

Driven by a need to find low-cost energy solutions to meet anticipated demands arising from increased robotic and human cislunar activities, the extraction and utilization of naturally occurring volatiles found on the lunar surface is an area of growing interest to both the private and public space sectors. The use of hydrogen and oxygen extracted from accumulations of water is viewed as particularly promising. Several lines of evidence point to the presence of water, possibly in the form of water ice, stored within cold trap reservoirs in the permanently shadowed regions (PSRs) of the northern and southern poles of the Moon. The type and spatial resolution of available datasets however prevent evaluation of resource potential on a scale relevant to address geological uncertainties and assess the technological and economic feasibility of water resource extraction for use by an in-space market. Surface field exploration is required to reduce investment risk; however the success of resource exploration activities will depend on the selection of appropriate exploration methods. To address this we introduce the application of play-based exploration (PBE) techniques, a resource exploration approach commonly used by the terrestrial petroleum and geothermal energy industries to direct decision making regarding high-risk ventures. Applied to the Moon this method seeks to identify locations where exploration activities are most likely to encounter an economically/commercially viable quantity of water guided by the geological concepts of delivery, trapping, and storage of water molecules within a reservoir. In this study we examine the critical geological uncertainties in the reservoir system model and provide recommendations for resource exploration approach, data collection, and analysis techniques.

Zoonoses As Ecological Entities: A Case Review of Plague.

As a zoonosis, Plague is also an ecological entity, a complex system of ecological interactions between the pathogen, the hosts, and the spatiotemporal variations of its ecosystems. Five reservoir system models have been proposed: (i) assemblages of small mammals with different levels of susceptibility and roles in the maintenance and amplification of the cycle; (ii) species-specific chronic infection models; (ii) flea vectors as the true reservoirs; (iii) Telluric Plague, and (iv) a metapopulation arrangement for species with a discrete spatial organization, following a source-sink dynamic of extinction and recolonization with naïve potential hosts. The diversity of the community that harbors the reservoir system affects the transmission cycle by predation, competition, and dilution effect. Plague has notable environmental constraints, depending on altitude (500+ meters), warm and dry climates, and conditions for high productivity events for expansion of the transmission cycle. Human impacts are altering Plague dynamics by altering landscape and the faunal composition of the foci and adjacent areas, usually increasing the presence and number of human cases and outbreaks. Climatic change is also affecting the range of its occurrence. In the current transitional state of zoonosis as a whole, Plague is at risk of becoming a public health problem in poor countries where ecosystem erosion, anthropic invasion of new areas, and climate change increase the contact of the population with reservoir systems, giving new urgency for ecologic research that further details its maintenance in the wild, the spillover events, and how it links to human cases.

Climate change impacts on water management and irrigated agriculture in the Yakima River Basin, Washington, USA

The Yakima River Reservoir system supplies water to ~180,000 irrigated hectares through the operation of five reservoirs with cumulative storage of ~30% mean annual river flow. Runoff is derived mostly from winter precipitation in the Cascade Mountains, much of which is stored as snowpack. Climate change is expected to result in earlier snowmelt runoff and reduced summer flows. Effects of these changes on irrigated agriculture were simulated using a reservoir system model coupled to a hydrological model driven by downscaled scenarios from 20 climate models archived by the 2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. We find earlier snowmelt results in increased water delivery curtailments. Historically, the basin experienced substantial water shortages in 14% of years. Without adaptations, for IPCC A1B global emission scenarios, water shortages increase to 27% (13% to 49% range) in the 2020s, to 33% in the 2040s, and 68% in the 2080s. For IPCC B1 emissions scenarios, shortages occur in 24% (7% to 54%) of years in the 2020s, 31% in the 2040s and 43% in the 2080s. Historically unprecedented conditions where senior water rights holders suffer shortfalls occur with increasing frequency in both A1B and B1 scenarios. Economic losses include expected annual production declines of 5%–16%, with greater probabilities of operating losses for junior water rights holders.

Climate change impacts on water management in the Puget Sound region, Washington State, USA

Climate change is projected to result, on average, in earlier snowmelt and reduced summer flows in the Pacific Northwest, patterns not well represented in historical observations used in water planning. We evaluate the sensitivities of water supply systems in the Puget Sound basin cities of Everett, Seattle, and Tacoma to historical and projected future streamflow variability and water demands. We simulate streamflow for the 2020s, 2040s, and 2080s using the distributed hydrology–soil–vegetation model (DHSVM), driven by downscaled ensembles of climate simulations archived from the 2007 IPCC Fourth Assessment Report. We use these streamflow predictions as inputs to reservoir system models for the three water supply systems. Over the next century, under average conditions all systems are projected to experience declines and eventual disappearance of the springtime snowmelt peak. How these shifts affect management depends on physical characteristics, operating objectives, and the adaptive capacity of each system. Without adaptations, average seasonal drawdown of reservoir storage is projected to increase in all three systems throughout the 21st century. Reliability of all systems in the absence of demand increases is robust through the 2020s however, and remains above 98% for Seattle and Everett in the 2040s and 2080s. With demand increases, however, reliability of the systems in their current configurations and with current operating policies progressively declines through the century.

Models and Realities of Reservoir Operation

Social preferences for uses of water invariably change with time, and the purposes and priorities for which existing reservoirs are operated may likewise change. Moreover, because new reservoir construction in the United States has not kept pace with growing demands on water and storage, the need for improved operational efficiency has never been greater. Operational models have a long history of success both in planning and real-time decision support applications, disclosing opportunities for conjunctive use of reservoirs and efficient allocations of water and storage. Since the late 1950s, for example, the Streamflow Synthesis and Reservoir Regulation SSARR model has provided invaluable decision support for planning and real-time control of the Columbia River Basin. For nearly three decades the Corps of Engineers HEC-5 model was the most widely applied in the world for all-purpose reservoir system operational planning, its success spawning a new generation of integrated tools designed for shared-vision applications. Occasionally, performance and efficiency gains promised by models used for operational planning may fail to materialize in practice, with consequences ranging from missed opportunities for water management policy consensus to public water supplies placed at risk, as happened in Atlanta in 2007. Models are here to stay, but their practical utility is best assured by appreciation of their intrinsic limitations, care in preparation of their input data, and circumspection in interpretation of their results. The proposition that all models at some level simplify reality predates computer models, a by-product of the fall of mathematical formalism beginning in 1931 with Czech logician Kurt Godel’s incompleteness theorems. To paraphrase the eminent statistician George Box, “Essentially, all models are wrong, but some are useful.” For models to be useful, however, users must understand their limitations and temper expectations accordingly—take them with a grain of salt, so to speak. This can present a challenge with complex models of complex systems. Numerical models of complex physical phenomena, such as flow of water or forces on structures, approximate solutions to differential equations for which no analytical solutions presently exist. Unknown, unmeasured, and uncertain quantities are often lumped into empirical coefficients, which may be adjusted to ensure the solution is “conservative” relative to its intended use or to provide an added margin of safety in design. For models that simulate interdependent hydraulic, hydrologic, and human decision-making aspects of reservoir operation, however, conservatism may be a slippery concept to define, and instances of clearcut operational “failure” too infrequent for reliable estimation of appropriate factors of safety. It is easy to imagine, for example, why sound flood management practice, seeking to minimize water in storage for protection against future floods, would not be conservative when applied to drought management strategies seeking to maximize water in storage to augment reliable water supply. Continuity is normally the most easily satisfied requirement of reservoir system models. Even so, seepage, leakage, inaccurate reservoir outlet works and river rating curves, evapotranspiration, and unaccounted water diversions and returns can introduce significant errors to hydrologic time-series inputs to reservoir models. Analysis of model sensitivity to these uncertainties may be complicated by extraneous factors, and the potential for bias depends upon how errors accumulate in simulated utilization of system storage. Operational models are also called upon to replicate patterns and timing of reservoir release decisions realistically enough for design, operational planning, and/or real-time water control decision support. This is a much more difficult proposition than mere mass balance, given that reservoir operators unlike models know that they do not have perfect information and consequently temper release decisions using estimates, forecasts, hedging, and plain intuition. In economics, imperfect information and uncertainty increase transaction costs and thus tend to prevent optimal outcomes Williamson 2006; the same applies to reservoir operation. Operational models simulate “perfect” rule-compliant releases given well-defined rules and accurate information on the current state of the system. Models may even accommodate uncertainty with probabilistic inputs, but bias is another matter. Sequential simulation may fail to disclose, for example, the range of possible outcomes when hydroclimatic trends and variability are not adequately represented in time-series inputs. Climate change considerations aside, periods of record of historical system inflows may not be sufficient to capture hydrologic extremes high and low flows of long-run cycles, a phenomenon known as trenddependent autocorrelation. In such cases, models may understate conservation or flood storage required to reliably meet operational objectives. Inadequate period of hydrologic record was identified as a contributing factor in contemporary findings of overallocated

The modular modeling system (MMS) — The physical process modeling component of a database-centered decision support system for water and power management

The Modular Modeling System (MMS) is an integrated system of computer software that is being developed to provide the research and operational framework needed to support development, testing, and evaluation of physical-process algorithms, and to facilitate integration of user-selected sets of algorithms into operational physical-process models. MMS uses a module library that contains compatible modules for simulating a variety of water, energy, and biogeochemical processes. A model is created by selectively linking modules from the library using MMS model-building tools. A geographic information system (GIS) interface also is being developed for MMS to support a variety of GIS tools for use in characterizing and parameterizing topographic, hydrologic, and ecosystem features, visualizing spatially and temporally distributed model parameters and variables, and analyzing and validating model results. MMS is being coupled with the Power Reservoir System Model (PRSYM) to provide a database-centered decision support system for making complex operational decisions on multipurpose reservoir systems and watersheds. The U.S. Geological Survey and the Bureau of Reclamation are working collaboratively on a project titled the Watershed Modeling Systems Initiative to develop and apply the coupled MMS — PRSYM models to the San Juan River basin in Colorado, New Mexico, Arizona, and Utah.

Dissolved oxygen in streams and reservoirs

Dissolved oxygen in streams and reservoirs