Large-scale Reservoir Research Articles

Formation conditions and exploration direction of large natural gas reservoirs in the oil-prone Bohai Bay Basin, East China

Abstract The Bohai Bay Basin is a typical oil-prone basin, in which natural gas geological reserves have a small proportion. In this basin, the gas source rock is largely medium-deep lake mudstone with oil-prone type II2-II1 kerogens, and natural gas preservation conditions are poor due to active late tectonic movements. The formation conditions of large natural gas fields in the Bohai Bay Basin have been elusive. Based on the exploration results of Bohai Bay Basin and comparison with large gas fields in China and abroad, the formation conditions of conventional large-scale natural gas reservoirs in the Bohai Bay Basin were examined from accumulation dynamics, structure and sedimentation. The results show that the formation conditions of conventional large natural gas reservoirs in Bohai Bay Basin mainly include one core element and two key elements. The core factor is the strong sealing of Paleogene “quilt-like” overpressure mudstone. The two key factors include the rapid maturation and high-intensity gas generation of source rock in the late stage and large scale reservoir. On this basis, large-scale nature gas accumulation models in the Bohai Bay Basin have been worked out, including regional overpressure mudstone enriching model, local overpressure mudstone depleting model, sand-rich sedimentary subsag depleting model and late strongly-developed fault depleting model. It is found that Bozhong sag, northern Liaozhong sag and Banqiao sag have favorable conditions for the formation of large-scale natural gas reservoirs, and are worth exploring. The study results have important guidance for exploration of large scale natural gas reservoirs in the Bohai Bay Basin.

Formation conditions and exploration direction of large and medium gas reservoirs in the Junggar Basin, NW China

Abstract The Junggar Basin is rich in oil but lacks natural gas, which is inconsistent with its geological background of natural gas. Based on the analysis of main source kitchens, and the evaluation of geological setting and controlling factors of gas accumulation, it is proposed that three significant fields for gas exploration should be emphasized. The first field is the Carboniferous volcanic rocks. The Carboniferous residual sags and large-scale reservoirs were developed in three active continental margins, i.e., the southeastern, northeastern and northwestern active continental margins. Gas accumulation is controlled by the favorable reservoir-caprock combinations composed of volcanic rocks and their superimposed lacustrine mudstones in the Upper Wuerhe Formation. Dinan, Eastern and Zhongguai uplifts are three favorable directions for natural gas exploration. The second field is the Lower combinations in the southern margin of Junggar Basin. Rows of structural traps were developed in this area with ideal preservation conditions and space-time configuration for trap-source combinations. Sets of clastic reservoirs and overpressured mudstones formed perfect reservoir-caprock combinations which are the main exploration direction for Jurassic coal-type gas reservoirs in this area. The seven large structural traps in the middle-east section are recently the most significant targets. The last field is the Central Depression. Large hydrocarbon generating centers, i.e., Mahu, Fukang and Shawan sags, were developed in this area, their source rocks were deeply buried and at highly-mature stage. Thus the Central Depression is a favorable exploration direction for Permian high-over mature gas fields (reservoirs). Great attentions should be paid to two types of targets, the deeply–buried structures and structural-lithologic traps. Based on three main gas systems, gas exploration is suggested be strengthened within three fields and on three levels.

The public's perception of run-of-the-river hydropower across Europe

A large share of future European hydropower projects will be run-of-the-river schemes. To understand the potential for RoR hydropower development and modernization of the technology as an opportunity for sustainable decentralization, we use the Q-methodology to compare public values about RoR hydropower in German, Portuguese and Swedish case studies. Four perspectives on the importance of RoR hydropower emerged from our analysis: (i) maintain regional control, (ii) fight climate change, (iii) promote citizen well-being and (iv) protect natural ecosystems. Strong preferences for regional control imply RoR should be managed as distributed generation rather than viewed as part of a centralized, national system like traditional large-scale reservoir hydropower. Based on the importance of citizen well-being and ecological measures, operators could adopt strategies such as river widening and the reconstruction of secondary channels, which help control floods, create recreational opportunities as well as enhance ecological habilitation and biodiversity. Additionally, policymakers could support rigorous monitoring programs to assess the ecological impact of RoR.

Compositional Modeling of Carbonate Acidizing Processes with CO2 Evolution in Aqueous Environments

Summary Several modeling studies have been conducted in carbonate acidizing, particularly in the area of aqueous environments. Yet, complete understanding of this complex subsurface process remains elusive. Characterizing the effects of evolved CO2, a product of the chemical reaction between carbonates and HCl (hydrochloric acid), has been ignored to date under the assumption that high operating pore pressures keep CO2 completely dissolved in the surrounding solution. However, the presence of CO2 in the porous media of the formation itself changes fluid-flow dynamics throughout the entire system. This paper describes a numerical simulation study to accurately model the physics of carbonate acidizing. A validation of the model is conducted by replicating experiments described in the published literature and by performing laboratory coreflood experiments of carbonate acidizing. The acid efficiency curve and initial pore pressure variations for single-phase experimental studies from the literature is matched by including the effects of evolved CO2 in the model. Two Indiana limestone cores of 6 in. length and 1.5 in. diameter were used to conduct (1) a tracer-injection study with 5 wt% KCl (potassium chloride) solution and (2) an acid-injection study with 15 wt% HCl solution. The experiments were conducted at 72°F, and 1,180 psi pore pressure. The Indiana limestone cores were characterized via computed tomography (CT) scans, and a detailed, accurate porosity profile of each core was used as input to the numerical model. The tracer fluid was used to characterize the porous environment and mechanical dispersion coefficients, and for subsequent calibration of the simulation model. From the conducted single-phase acidizing coreflood experiment, pressure drop values across the core were closely monitored with time to assess acid breakthrough, and the core effluent samples were collected at regular intervals and analyzed to determine the concentrations of calcium chloride (CaCl2) and HCl. CT scans of each core conducted post-acidizing describe its wormhole pattern. These parameters are accurately matched using the simulation model. A high pore pressure of 1,000 psi and above is not sufficient to keep all the evolved CO2 in solution during carbonate acidizing. The presence of CO2 as a separate phase hinders acid efficiency. Up to 24% by volume of pore space is shown to be occupied by the evolved CO2 that exists as a separate phase, and is located ahead of the acid front during the acidizing process, thus competing for flow with the incoming acid. The modeling of CO2 as a component for simulating the acid coreflood played a key role in acquiring a better match with experimental results, with limited dependency on empirical pore-scale parameters. In addition to wormhole propagation, the current model accurately forecasts effluent concentrations collected and quantity of rock dissolved from the acidized porous media. A new approach to accurately predict carbonate acidizing in porous media for an aqueous environment has been presented via compositional modeling using a reservoir simulator. The presented methodology can be incorporated in large field scale reservoir models.

Characteristics and genetic mechanism of large granitic buried-hill reservoir, a case study from PengLai oil field of Bohai Bay Basin, north China

In recent years, a major breakthrough has been made in granite hydrocarbon exploration in the Bohai Bay Basin. With the proven reserves of more than 2 × 108 t, the Penglai (PL) oilfield is the largest granite oilfield discovered in China. Although the reservoir scale is large, the reservoir heterogeneity is also strong, which brings challenges to its exploration and evaluation. Based on the data of cores, thin sections, whole rock and physical property, the reservoir characteristics and control factors of reservoir-forming in the study area are discussed through the fault analysis and the recovery of tectonic uplift history. The results show that the lithology of PL structure are mainly Mesozoic intrusive granite and Proterozoic mica quartz schist, which develops reservoirs related to the weathered crust and internal fractures. Due to the influence of weathering intensity and fault activity, the porous reservoirs in weathered glutenite zone, pore-fractured reservoirs in weathered fracture zone and fractured reservoirs in the inner fracture zone were distributed orderly from top to bottom vertically. The scale of the high quality reservoir on the plane is controlled by lithology, faults, weathering and buried depth. Granite is the main reservoir-forming lithology for more brittle and less resistant to weathering than mica quartz schist, which forms a special phenomenon that the granite in saddle is rich for hydrocarbon while the mica quartz schist in high position is poor for hydrocarbon accumulation. The northwest Miaoxi fault is the main controlling-fault in the study area, and there is an obvious negative correlation between reservoir thickness and distance from this fault. The long-term uplift of Cenozoic provides conditions for strong weathering, while the shallow burial in the late stage provides effective protection for weathered crust reservoirs. The coupling of the above conditions is the main reason of large scale reservoir development in the study area, and among them, the long-term uplift is the key factor for reservoir-forming.

Research Methods of Different Levels of Reservoirs Based on Seismic Data

The lack of drilling data is a difficult problem in the study of reservoir configuration under the condition of sparse well pattern. In this paper, the seismic data are fully excavated, and the methods of frequency RGB fusion, small scale river sand attribute fusion and horizontal well data combination are used to study the river level, the level point bar level, and the internal configuration of point bar. The frequency division RGB fusion method has a good effect on the characterization of large-scale channel reservoirs, especially the channel stacking period and channel boundary response. The integrated attributes of river channel and sand body distribution method has a good effect on depicting the small-scale end river channel and abandoned river channel, and on this basis, the research on point bar sand body is consistent with the actual drilling. The high-precision edge detection section and RGB fusion section are superimposed to display the development of lateral volume, and verify with the actual horizontal well. River facies reservoirs of different scales have been verified by drilling with targeted research techniques. The results show that under the condition of sparse well pattern, well-seismic combination is the key to the division of small-scale sedimentary units, multi-attribute fusion under high-resolution seismic data is an important means to identify and depict point bar and abandoned river channels, and the application of horizontal well data is a supplementary means to test results and depict lateral accumulation. The research results have achieved good application results in guiding the actual production of oil field.

Determining the most effective flow rising process to stimulate fish spawning via reservoir operation

Various studies have shown that stream flow regimes play a significant role in fish spawning stimuli. Stream flows have been altered by reservoir operations around the world, especially in arid and semi-arid regions. In this study, the flow rising processes most effective for fish spawning stimuli are identified, and their quantitative characteristics are then represented by a set of hydrological indices. Based on a quantitative ecological scoring method describing the statistical similarity between the reservoir release and the natural flow regime, a multi-objective optimization model considering hydropower generation and fish habitat protection is proposed and then solved by the Non-dominated Sorting Genetic Algorithm (NSGA-II). The proposed methodology is applied to a large-scale reservoir on the upper reaches of the Yellow River in China. The statistics of these indices verify the regulations on the flow rising processes in fish spawning seasons via reservoir operation in different hydrological years. The Pareto Front derived from the multi-objective optimization indicates that it is possible to both improve the local ecology and increase hydropower generation profits using the method proposed herein on the basis of proper understanding of the effective flow process required by fish.

Distributed Gauss-Newton Optimization with Smooth Local Parameterization for Large-Scale History-Matching Problems

Summary Finding multiple posterior realizations through a reservoir history-matching procedure is of significance for uncertainty quantification, risk analysis, and decision making in the course of reservoir closed-loop management. Previously, an efficient, distributed, optimization algorithm—global linear-regression (GLR) with distributed Gauss-Newton (GLR-DGN)—has been proposed in the literature to iteratively minimize multiple objective functions by performing Gauss-Newton (GN) optimizations concurrently while dynamically sharing information between dispersed regions in a reduced parameter space. However, theoretically, the required number of initial training models should be larger than the number of parameters to guarantee a unique solution for the GLR equation for sensitivity-matrix estimation. This limitation makes the large-scale reservoir history-matching problem with a large amount of parameters almost intractable. We enrich the previous history-matching framework by integrating our recently proposed smooth local parameterization (SLP) and DGN for the sensitivity-matrix calculation. Motivated by the fact that one specific flow response mainly depends on a few influential or local parameters, which can be generally identified by the physical position of the wells (e.g., the parameters in the zone surrounding the wells), which is particularly true for large-scale reservoir models, this paper presents a new integration of subdomain linear-regression (SLR) with DGN, referred to as SLR-DGN. This SLP allows us to independently represent the globally spatial parameter field within low-order parameter subspaces in each subdomain. On the basis of the SLP procedure, only a few training models are required to compute local sensitivity of the response functions using a subdomain linear regression. SLP is a linear transformation with smoothness and differentiability, which makes it particularly compatible with Newton-like gradient-based optimization algorithms. Furthermore, we also introduce an adaptive scheme, named weighting smooth local parameterization (WSLP), in which the minimization algorithm adaptively determines the weighting coefficients and the optimal domain decomposition (DD) correspondingly, to mitigate the negative effects of an inappropriate DD strategy. We support our framework with numerical experiments for a four-variable toy model and a modified version of the sensitivity analysis of the impact of geological uncertainties on production (SAIGUP) model with spatially dependent parameters. Comparisons with previous GLR-DGN have shown that our new framework can generate comparable and even better results with significantly reduced computational cost. This SLP has high scalability, because the number of training models depends primarily on the number of local parameters in each subdomain and not on the dimension of the underlying full-order model. Activating more subdomains results in fewer local parameter patterns and enables us to run fewer training models. For a large-scale case study in this work, to optimize 412 global parameters, SLR-DGN needs only 100 initial-model simulations. In comparison to GLR-DGN where the parameters are defined over the entire domain, the central-processing-unit cost is reduced by a factor of several orders of magnitude, while retaining reasonable accuracy.

A black-oil approach to model produced gas injection in both conventional and tight oil-rich reservoirs to enhance oil recovery

A robust compositionally extended black-oil simulation approach is developed, which is capable of including the effect of large gas-oil capillary pressure for first contact miscible (FCM), and immiscible gas injection. The simulation methodology is applied to gas flooding in both high and very low permeability reservoirs. For a high permeability conventional reservoir, simulations use a five-spot pattern with different reservoir pressures to mimic both FCM and immiscible displacements. The results show that the simple modified black-oil approach can model well both immiscible and miscible floods, as long as the minimum miscibility pressure (MMP) is matched. For a tight oil-rich reservoir, primary depletion and huff-n-puff gas injection are simulated including the effect of large gas-oil capillary pressure in flow and in flash calculation on recovery. Finally, a dynamic gas-oil relative permeability correlation that accounts for the compositional changes owing to the produced gas injection is introduced and applied to correct for changes in interfacial tension (IFT), and its effect on oil recovery is examined. The results show that the new black-oil approach can model these processes well and could be implemented when fully compositional simulations are computationally too time consuming. For the first time, a black-oil type reservoir simulation method is used to simulate near-miscible and immiscible produced gas injection enhanced oil recovery. It provides a fast and robust alternative for large-scale reservoir simulation with the purpose of flaring/venting reduction through reinjecting the produced gas into the reservoir for EOR.

Petroleum geological conditions and exploration potential of Lower Paleozoic carbonate rocks in Gucheng Area, Tarim Basin, China

Abstract Lower Paleozoic carbonate rocks are an important exploration area in craton area of the Tarim Basin, with the proven oil and gas reserves of more than 2.2×108 t, but no large-scale discovery has been made in the Gucheng area so far. The key issues restricting exploration are that the source rock, reservoir scale and law of oil and gas enrichment are unclear. By systematically examining the petroleum geological conditions of Lower Paleozoic carbonate rocks, the following findings are reached: (1) Source rocks of slope-basin facies developed in Cambrian-Lower Ordovician in the Gucheng area. (2) The dolomitized beach in the lower part of Ordovician Yingshan Formation has large-scale reservoirs, good reservoir-cap assemblage and developed gas source faults, and is an important field for increasing reserves and production in the near future; hydrocarbon enrichment is controlled by reservoir and gas source faults, and the central dolomitized beach zone is the main exploration area. (3) The Cambrian platform margin reef beach, large in scale, good in physical properties and close to source rocks, has the possibility to form monolithic gas field; the caprock and preservation conditions are the key factors for hydrocarbon enrichment; the northern part of the phases I and II platform margin reefs has better sealing conditions, and is the main direction of next exploration. (4) Limestone fault solution reservoirs in the upper part of Ordovician Yingshan Formation, controlled by faults and small in scale, but good in reservoir-cap combination, worth exploring. (5) The granular limestone beach of Ordovician Yijianfang Formation is well developed and gas-bearing, but short in exposure dissolution time, and the reservoirs are strongly heterogeneous, and are a potential exploration field.

Shifts in characteristics of the plant-soil system associated with flooding and revegetation in the riparian zone of Three Gorges Reservoir, China

The operation of the Three Gorges Reservoir (TGR), the largest hydropower dam in the world, has triggered a dramatic shift in the flooding regimes of sites upstream of the reservoir. Little is known about how disrupted flooding regimes and consequent management approaches might affect the ecological and biogeochemical characteristics of riparian ecosystems. In this study, we evaluated the effects of disruptions to natural flooding regime on basic soil properties, soil nutrient and heavy metal levels, and key characteristics of riparian plant and soil microbial communities. To do this, we used an elevational gradient that encompassed four flooding duration zones (0 (i.e., control), 169, 237, 286 days of flooding per year on average). The disrupted flooding regimes were associated with levels of soil total N and P that were on average 17% and 24% lower, respectively, than those in the non-flooded areas. On the other hand, the concentrations of heavy metals (Hg, Pb, Cu, Zn and Mn) were higher in flood-affected areas than in the non-flooded areas. Increased flooding frequency was also associated with lower plant diversity and species richness relative to non-flooded areas. Thus, disruption of the natural flooding regime had strong and often negative consequences for the ecological and biogeochemical properties of the riparian ecosystems in our study. There was some evidence that riparian plant communities were able to partially recover from prior flooding during a single growing season, even after nine years of repeated flooding, and these recovery trajectories were associated with shifts in soil chemical properties during the same period. However, revegetation efforts had few effects on ecosystem properties or their recovery trajectories following flooding events, suggesting that natural regeneration could be a useful option for the management of these sites. We conclude that the unnatural flooding regimes associated with large scale reservoir development are likely to have profound impacts on the structure and functioning of riparian ecosystems, and these will pose a considerable challenge for environmental management and biodiversity conservation.

From Atoms to Pre-salt Reservoirs: Multiscale Simulations of the Low-Salinity Enhanced Oil Recovery Mechanisms

The goal of this review paper is two-fold: bringing an updated survey on the literature of the proposed mechanisms behind the low-salinity enhanced oil recovery (EOR) and propose ways to model them based on simulations coupling atomic to reservoir scales. The low salinity water injection (LSWI) presents some advantages over other EOR techniques since it is a cost-effective method, has no inherent environmental damage and does not affect the subsequent stages of crude oil treatment and refinement. The LSWI is particularly interesting for exploration and production on pre-salt carbonate reservoirs. We couple the LSWI mechanisms with molecular modeling methodologies, addressing their use to describe the EOR via LSWI. From the molecular modeling, one can obtain parameters for the large-scale reservoir simulators, thus, improving their accuracy. Therefore, the molecular modeling approaches are complementary tools to optimize the EOR via LSWI. Among all the involved mechanisms on the LSWI, the wettability alteration is pointed out by several authors as the fundamental one, to explain the EOR. However, there are controversies related to its cause: salting-in effect, multi-component ionic exchange, pH alteration, electric double layer expansion, fines migration, limited release of particles and osmotic pressure are among the main proposals. In this sense, several molecular modeling techniques have been explored to foster theories that explain the possible mechanisms and optimize the oil production combining the molecular dynamics simulations and Ab initio calculations with reservoir simulators.

Real-time reservoir operation using recurrent neural networks and inflow forecast from a distributed hydrological model

Large-scale reservoirs play an essential role in water resources management for agriculture irrigation, water supply and flood controls. However, we need robust reservoir operation systems under both normal flow and extreme flow conditions. In this study, we applied recurrent neural networks (RNN) to simulate the operation of three multi-purpose reservoirs located in the upper Chao Phraya River basin. Two reservoirs have the function of multiannual flow regulation and one has the function of incomplete annual regulation. The goal of this study is to explore the applicability of RNN models for operation of reservoirs with multiannual flow regulation under different flow regimes, especially under extreme floods and droughts. We used three RNNs, namely nonlinear autoregressive models with exogenous input (NARX), long short-term memory (LSTM) and genetic algorithm based NAXR (GA-NAXR) for reservoir operation based on historical data. For real-time water resources management, an accurate inflow forecast is required to provide a real-time reservoir outflow, and thus we also carried out a real-time reservoir operation using the RNN and the inflow forecast by a distributed hydrological model. Results show that (1) GA-NARX has the highest accuracy among three RNNs and is more stable than the original NARX by optimizing the initial conditions, although it takes longer training time than NARX and LSTM; (2) GA-NARX-based operation model is effective under extreme floods and droughts; and (3) the real-time operation system combining the GA-NARX and the distributed hydrological model has reasonable accuracy in both wet season and dry season. RNN-based operation model developed in this study has potential applicability in practical water management, and the model combining the hydrological prediction is specially useful for real-time reservoir operation.

Averaging the experimental capillary pressure curves for scaling up to the reservoir condition in the imbibition process

Heterogeneity of a reservoir rock is an important factor that needs to be accounted for modeling of reservoir blocks. The rock properties are measured in the laboratory using a small core plug while in the simulation of a large scale reservoir, the size of each grid block is much larger. Hence, the rock properties of a simulation block should be obtained by averaging methods from core samples that forms the grid block. Among the rock properties, capillary pressure (Pc) is more challenging as it is a function of fluids' saturation. The most commonly used methods to average the capillary pressure data are J-function and simple curve fitting. However, these methods are not adequately precise and the heterogeneity pattern, and the physics of fluids' flow are not considered as well.In the present paper, various models were built using experimental data under different heterogeneity patterns, and then the imbibition process of the oil/water system was simulated. In this case, different Pc curves were distributed in the model based on the heterogeneity patterns. In the next step, one Pc curve, obtained from an averaging method, was assigned to the entire model and the simulation was applied again. The comparison between the simulation results of the actual model and the averaged Pc model, depicts the accuracy of the averaging method.We introduced and tested different averaging techniques for many heteronomous models and the accuracy of each technique was evaluated. The results show that the traditional techniques are inaccurate and may not represent the heterogeneous (actual) model. Based on the results obtained from many models, a new approach is proposed for the averaging of the Pc curves which can adequately predict the actual model's Pc. This method was successfully verified for a variety of models which had not been used in the development stage.

Ensemble of constraint-handling techniques for solving reservoir scheduling problems

Abstract Reservoir scheduling based on evolutionary algorithms needs to handle potentially stringent physical and operational constraints. Both generic and reservoir scheduling problem-specific constraint-handling techniques (CHTs) have their own merits and limitations. No CHT currently available can yield better solutions than the others consistently. To ensure good reservoir operation schedules, we develop an ensemble of CHTs (ECHT) that can utilize the advantages of different individual CHTs. In the ensemble, each CHT has its own population. In every generation, the different offspring populations are mixed together and evaluated. Each CHT then assigns fitness to all individuals and selects some of them to form its new parent population. The ECHT has been tested against long-term hydropower scheduling of two large-scale reservoir systems in China. Results show that the ECHT outperforms the state-of-the-art CHTs, and its probability of returning feasible solutions is much higher. The reservoir levels optimized with the ECHT are well suited for hydropower generation, which also reduce the chance of reservoir spilling.

Ensemble size investigation in adaptive ES-MDA reservoir history matching

In this work, we study the ensemble size influence on an adaptive ensemble-based methodology for history matching of petroleum reservoirs. The assimilation scheme used is an adaptive ensemble smoother with multiple data assimilation (ES-MDA) in which both the total number of assimilations and the inflation factor of each iteration are defined automatically by the algorithm. This fact leads to the assumption that the predefined algorithm parameters may have influence in the total number of assimilations and the inflation factors. One main parameter that can be investigated is the number of ensemble members used in the assimilation, also called ensemble size. The ensemble size influence was analyzed by applying the adaptive ES-MDA in a synthetic large-scale reservoir model. As a result of the investigation, the ensemble size showed influence on the reduction in the uncertainty of the posterior models, but it did not show any influence on the total number of assimilations and on the inflation factor selection.

Characterization of three-dimensional channel reservoirs using ensemble Kalman filter assisted by principal component analysis

sEnsemble-based analyses are useful to compare equiprobable scenarios of the reservoir models. However, they require a large suite of reservoir models to cover high uncertainty in heterogeneous and complex reservoir models. For stable convergence in ensemble Kalman filter (EnKF), increasing ensemble size can be one of the solutions, but it causes high computational cost in large-scale reservoir systems. In this paper, we propose a preprocessing of good initial model selection to reduce the ensemble size, and then, EnKF is utilized to predict production performances stochastically. In the model selection scheme, representative models are chosen by using principal component analysis (PCA) and clustering analysis. The dimension of initial models is reduced using PCA, and the reduced models are grouped by clustering. Then, we choose and simulate representative models from the cluster groups to compare errors of production predictions with historical observation data. One representative model with the minimum error is considered as the best model, and we use the ensemble members near the best model in the cluster plane for applying EnKF. We demonstrate the proposed scheme for two 3D models that EnKF provides reliable assimilation results with much reduced computation time.

Geological impact of the Three Gorges Reservoir on the Yangtze River in China

The Three Gorges Reservoir (TGR), located on the Yangtze River in China, currently holds the title as the biggest man-made water reservoir in the world. However, with its unprecedented size, construction has brought with it natural gas blowout incidents in nearby mining wells, a geological phenomenon that had not been considered before. These incidents had resulted in the loss of hundreds of lives as well as millions of dollars in properties. Through investigation, various hypotheses which suggest that the blowouts were indeed related to the reservoir are proposed. In addition, TGR’s size has made it a suitable target for quantifying and understanding various well-established side-effects that result from the creation of new reservoirs. Such ‘common’ effects that are considered include reactivated landslides and reservoir-induced earthquakes. From this, it is proposed that initial impoundment of water increases landslide susceptibility for a period, whilst being independent of rainfall. From this paper, it could be better understood how large-scale reservoirs are able to impact surrounding areas geologically.

Evaluation of Environmental and Ecological Impacts of the Leading Large-Scale Reservoir on the Upper Reaches of the Yellow River

Large-scale reservoirs have played a significant role in meeting various water demands and socio-economic development, while they also lead to undeniable impacts on the environment and ecology. The Longyangxia reservoir located on the Yellow River is the first large-scale reservoir on the upper Yellow River with a control area of 18% of the entire Yellow River Basin. Since it was put into operation in 1987, it has made great contributions to the national economy for over 30 years. In this study, the socio-economic benefits of the Longyangxia reservoir in power generation, water supply, flood control, and ice prevention are investigated. More importantly, its impacts on the ecology and environment are also presented and analyzed, such as the impacts on river morphology, flow regimes, peak flow, fish, phytoplankton, and zooplankton. It can be concluded that the construction of the Longyangxia reservoir contributes greatly to socio-economic benefits, the water area nearby has formed a new ecological environment, and the trophic level of the aquatic environment has probably increased.

A fully implicit constraint-preserving simulator for the black oil model of petroleum reservoirs

Due to the rapid advancement of supercomputing resource, there is a growing interest in developing parallel algorithms for the large-scale reservoir simulation. In this paper, we present a parallel and fully implicit simulator for the black oil model based on the variational inequality (VI) framework, which can be used to enforce important mathematical and physical properties to obtain accurate constraint-preserving solutions. In other words, this framework ensures the predicted solution to stay within the physical range. In the proposed approach, the black oil model is reformulated as a variational inequality system that naturally satisfies the basic boundedness requirement of the solution, and then a fully implicit finite volume method is applied to discretize the model equations. In addition to that, a number of nonlinear and linear fast solver technologies, including a variant of inexact Newton methods and the domain decomposition based preconditioners, are employed to guarantee the robustness and parallel scalability of the simulator. A particular emphasis of the proposed framework is placed on the parallel and algorithmic performance of the variational inequality approach across large-scale and heterogeneous problems. Several numerical results pertaining to the problems in one, two and three dimensions are presented to illustrate the efficiency, robustness, and the overall performance of the fully implicit constraint-preserving simulator.