Chemical enhanced oil recovery (EOR) methods have received increased attention in recent years since they have the ability to recover the capillary trapped oil. Successful chemical flooding application requires accurate numerical models and reliable forecast across multiple scales: core scale, pilot scale, and field scale. History matching and optimization are two key steps to achieve this goal.
For history matching chemical floods, we propose a general workflow for multi-stage model calibration using an Evolutionary Algorithm. A comprehensive chemical flooding simulator is used to model important physical mechanisms including phase behavior, cation exchange, chemical and polymer adsorption and capillary desaturation. First, we identify dominant reservoir and process parameters based on a sensitivity analysis. The history matching is then carried out in a stage-wise manner whereby the most dominant parameters are calibrated first and additional parameters are incorporated sequentially until a satisfactory data misfit is achieved. Next, a diverse subset of history matched models is selected for optimization using a Pareto-based multi-objective optimization approach. Based on the concept of dominance, Pareto optimal solutions are generated representing the trade-off between increasing oil recovery while improving the efficiency of chemical usage. These solutions are searched using a Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally we implement a History Matching Quality Index (HMQI) with Moving Linear Regression Analysis to evaluate simulation results from history matching process. The HMQI provides normalized values for all objective functions having different magnitude and leads to a more consistent and robust approach to evaluate the updated models through model calibration.
Zhang, Bo (School of Petroleum Engineering at China University of Petroleum & Texas A&M University) | Guan, Zhichuan (China University of Petroleum) | Lu, Nu (China University of Petroleum) | Hasan, A. R. (Texas A&M University) | Xu, Shenqi (China University of Petroleum) | Zhang, Zheng (University of Louisiana at Lafayette) | Xu, Boyue (Texas A&M University) | Xu, Yuqiang (China University of Petroleum)
Sustained casing pressure brings heavy routine maintenance and management workload, impedes stimulation treatments such as fracture and threatens safe production. This paper uses numerical model to analyze rising process of sustained casing pressure and study how cement sealed integrity is damaged, finally controlling sustained casing pressure by improving cement properties.
Cement sealed integrity collapse is one of the main reasons of sustained casing pressure, which distributes widely in high-pressure gas fields and gas storage reservoirs. First, numerical model is built according to volume consistency and mass conservation law to study rising process of sustained casing pressure. This model cam also clarify the relationship between sustained casing pressure and cement sealed integrity. And then a nonlinear equation set is established to study the mechanism of cement sealed integrity collapse. This equation set is based on Culon-Morper rule and stress-displacement continuity law. It can calculate micro annulus caused by wellbore pressure change. Lastly, a numerical model is built to predict the sustained casing pressure caused by micro annulus. Through this model, the influencing law of every factor is analyzed to find effective measures to mitigate sustained casing pressure and improve cement sealed integrity. The numerical calculation indicates that pressure rising period becomes shorter as cement micro annulus increases. Micro annulus happens when tensile force exceeds cement bonding strength. Optimizing the cement Poisson's ratio, and elasticity modulus can prevent micro annulus. Meanwhile, the casing internal pressure change should be controlled and cement bonding strength must be increased. It can inhibit micro annulus by using self-healing cement, casing sand adhesion and expansion casing, thus preventing sustained casing pressure. The optimization of cement top can permanently control sustained casing pressure.
Zhang, Bo (China University of Petroleum & Texas A&M University) | Guan, Zhichuan (China University of Petroleum) | Lu, Nu (China University of Petroleum) | Hasan, A. R. (Texas A&M University) | Xu, Chuanbin (Tianjin Geothermal Exploration and Development-Designing Institute) | Xu, Shenqi (China University of Petroleum) | Liao, Hualin (China University of Petroleum) | Zhang, Zheng (University of Louisiana at Lafayette)
Horizontal well greatly propels the development of unconventional oil and gas. Considering the drilling safety and basic demand of hole cleaning, define length of horizontal well as extreme hydraulic extension length when the drilling fluid pump rate is equal to minimum cutting-carry pump rate and hole cleaning satisfied basic demand. Based on this concept, a prediction model is established according to the relationship among minimum cutting-carry pump rate, bottomhole pressure, circulation pressure loss and drilling pump pressure. This model considers the influence of cuttings on the hydrostatic column pressure, horizontal annular pressure drop and annular geometrical shape. And then this model is used to analyze the impact of well structure, formation property, drilling fluid property, hole cleaning degree and drilling parameters on extreme hydraulic extension length. On the above basis, a new index called ration of dispersion coefficient is introduced to evaluate the sensitivity of each factor. The sensitivity decreases as the sequence of cutting particle size, drilling fluid flow behavior index, acceptable cutting bed height, wellbore diameter, ROP(8-15 m/h), drilling fluid density, drilling string eccentricity, formation fracture pressure, drilling fluid consistency index, well vertical depth and ROP(1-8 m/h). Based on both mitigation effect and feasibility, cutting particle size, drilling fluid flow behavior index, acceptable cutting bed height and rate of penetration are worthy to optimize to prolong EHEL.
For newly developed shale oil reservoirs, it is a challenging task to arrive at reasonable long-term production forecasts due to both large uncertainties associated with reservoir parameters and short production history. Assisted history matching plays an important role in integrating key uncertainties in order to arrive at a calibrated production prediction.
In this paper, we present two workflows to utilize a stochastic history matching method to a multi-fracture horizontal well in Eagle Ford shale oil reservoir. First, we discuss the impact of reservoir properties, hydraulic fractures, microfracs, phase behavior and rock characteristics on production behavior using sensitivity analysis. Next, we use the key uncertainties to calibrate the model against historical data using genetic algorithms. Three different geo-models were considered in all cases. However, in one workflow, they were evolved separately while in another one, they were evolved as a group. Production forecasting based on updated models from both workflows were categorized into several groups using cluster analysis. Then, the suggested workflows were compared according to their advantages and limitations. The results indicated that for workflow I, inaccuracy in uncertainty ranges could results in an incomplete set of updated models during evolution. For workflow II, reasonable probability must be provided; otherwise good model for certain geo-models may be ignored because the results could be constrained by less-probable geo-models. For unconventional reservoirs with very short limited static and dynamic data, our proposed workflows provide a flexible framework for capturing key uncertainties. Thus, they can be applied flexibly for long-term production forecasting or for identifying key areas for further data acquisition.
Zhang, Zheng (Tianjin Research Institute of Water Transport Engineering) | Zuo, Shu-hua (Tianjin Research Institute of Water Transport Engineering) | Li, Bei (Tianjin Research Institute of Water Transport Engineering)
A fast search and rescue positioning support system for maritime accidents is developed based on the marine basic database of flow and spilling oil mathematical modeling and tidal current mathematical modeling under wind action using VC platform, Fortran program, MapInfo and MapX control technology. The mathematical models are integrated by dynamic link libraries (DLL) created by FORTRAN language. On the basis of the database, the visual system is developed, which has a friendly interface and nice visualization, with menus, toolbars and forms similar to Windows. Research results successfully applied in surface water particle trajectory simulation of Bohai Bay and oil spill accident of a tanker. The drift path and range are in line with the simulation results to get a good effect of verification.
Li, Bei (Tianjin Research Institute for Water Transport Engineering) | Zhang, Zheng (Tianjin Research Institute for Water Transport Engineering) | Zuo, Shuhua (Tianjin Research Institute for Water Transport Engineering. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology) | Zhang, Yun (Port Engineering Department, Tianjin University)
Based on the characteristic of the currents and sediments in the research area, a 2D numerical model for the current field by waves is established in the paper. The unstructured grids are applied to fit the boundaries of the Yangshan sea area and the regulation project, thus the calculation accuracy is improved. Verifications with the observed data indicate that the simulated results can reflect the current fields in the region. Based on the numerical model it is rechecked and reasearched the influence of branch blocking in different stages of northern port construction on the changing processes of hydrodynamic, including tide process, velocity and tidal prism, in the main channel waters and the branches. The paper is to provide the scientific basis for the construction of Yangshan Port’s subsequent engineering.
The Yangshan Deepwater Harbor lies in the Qiqu archipelago, which is located about 32 km northwest to Luchaogang Harbor in the Nanhui District, in northern Hangzhou Bay, and on the south side of the Yangtze Estuary, 86 km from the center of Shanghai（Fig. 1）. The Yangshan Deepwater Harbor is the first offshore deepwater harbor in China. The sea area is composed of southern and northern island chains. The southern island chain is from east to west starting from Dayangshan Island and the northern island chain is from northwest to southeast starting from Dawugui Island. The water depth of the main channel to Yangshan Harbor from Dayangshan Island to Dawugui Island is more than 10 m and Yangshan Harbor is the nearest deepwater harbor with natural advantages for Shanghai(ZUO et al., 2009a, 2009b, 2009c). The Yangshan sea area belongs to strong current flow and high suspended sediment concentration. The seabed evolution is aroused by suspended sediment transport