Liu, Shuangshuang (PetroChina) | Wei, Chenji (PetroChina) | Gao, Yan (PetroChina) | Li, Yong (PetroChina) | Luo, Hong (PetroChina) | Liu, Zhuo (PetroChina) | Xiong, Lihui (PetroChina) | Zheng, Jie (PetroChina) | Lou, Yuankeli (PetroChina)
The Middle East carbonate reservoirs are mostly reef flat sedimentary complexes, which are high heterogeneous and have extensive baffles. It brings great challenges to the efficient development of such reservoirs. Focus on the problem, a method of describing baffle distribution conjunctively using static and dynamic data is put forward in this paper. The distribution of baffles in the target formation is characterized based on core observation, well loggings, image logs, etc. Then, their impact towards reservoir performance is evaluated based on production data and dynamic surveillance data. Based on the study, it is acquired that cementation mainly controlled the upper baffles and compaction controlled the lower. Generally speaking, permeability of baffle is higher in the crest area and lower in the flank area. Baffles are stably distributed throughout the reservoir, although their ability to block fluid flow varies from region to region. The existence of baffles and their ability to block fluid flow had impact to the development effect, so development optimization and scheme comparison carried out. The corresponding development strategies are proposed for reservoirs with extensive baffles. Injectors and producers with highly-deviated well-type will help establish effective displacement system and achieve better reservoir production, it can improve the development effect and enhance oil recovery. This study offers a comprehensive case study for engineers and geologists to better understand this reservoir, it also provides a methodology that can be referred when developing similar fields.
Carbonate reservoirs accounted for about 40% of the world's total oil and gas reserves, and oil and gas production accounted for about 60% of the total output [Roehl P O et al. 1985]. About 80% of the oilbearing formations in the Middle East are carbonate rocks, and the oil and gas production accounts for nearly 2/3 of the world output [Alsharhan A S et al. 1997]. Carbonate reservoirs contain more than 50% of the world's conventional oil and gas reserves, and generally have relatively low recovery rates [S.K.Masalmeh et al. 2012].
Carbonate reservoir types are diverse, and different types of reservoirs have great difference in permeability characteristics [Zhang Ningning et al. 2014]. The carbonate reservoirs in China mainly include fractures and fractured-cavity carbonates, the displacement mechanism of which is mainly carried out on the fractured-cavity media [Jin Zhijun et al. 2010, Liu Xiao-lei et al. 2017]. The large-scale carbonate reservoir in the Middle East is mailly reef-flat sedimentary complex, and the distribution of reservoir properties in the plane and in the vertical direction is very complicated [Bai Guoping 2007]. The heterogeneity is serious in lithology, physical property and reservoir scale [Jia Ailin et al. 2013]. The baffles are non-permeable or low-permeability layer sandwiched between the smallest cells in which the regional contrast can be performed [Cui Jian et al. 2013]. The existence of baffles strengthens the heterogeneity of the reservoir and makes the relationship between oil and water movement complex and changeable, which is one of the main factors affecting the reservoir development effect [Han Rubing et al. 2014].
Carbonate reservoirs are of strong heterogeneity. Their geological features and dynamic behaviors vary significantly for different types of carbonates. Characterizing the distribution of different types of carbonates and proposing different development strategies are critical for a successful development of carbonate reservoirs. This paper focuses on a super-giant carbonate reservoir with OOIP (Original Oil in Place) of more than 20 billion barrels. However, it has been naturally depleted over the past 40 years. Its reservoir pressure is approaching the bubble point pressure. Therefore, it is critical and urgent to propose optimized water flooding plan for this reservoir.
In this paper, the dataset includes seismic data, well logs, production history, dynamic surveillance data, et al. Firstly, three reservoir types are characterized as good, medium and poor reservoirs based on static and dynamic data. Then, the stacking patterns of different reservoir types are concluded and their distributions are determined, which provide us the foundation to propose customized water flooding plan. Finally, the water flooding performances of different stacking patterns are analyzed and full-field development strategies are proposed based on fine-scale geological modeling and numerical simulation.
Results indicate that stacking pattern has intimate relationship with facies map. For example, the distribution of stacking pattern A, in which good reservoir accounts for the majority, is consistent with the distribution of favorable grainstone shore facies, indicating very good reservoir quality that resulted in higher production rate, longer stable production period, and slow decline. In addition, different offtakes, well patterns, pressure maintenance, well types of different reservoir stacking pattern are determined based on the simulation results and distribution of different stacking patterns. The EUR is increased by more than 20% compared with natural depletion.
This paper offers a reference case of grouping different types of reservoirs and proposing customized water flooding plan, which help engineers and geologists to better develop other similar fields.
Wei, Chenji (PetroChina) | Wang, Yuhe (Texas A&M University at Qatar) | Ding, Yutao (PetroChina) | Li, Yong (PetroChina) | Shi, Jing (PetroChina) | Liu, Shuangshuang (PetroChina) | Tian, Changbing (PetroChina) | Li, Baozhu (PetroChina) | Xiong, Lihui (PetroChina) | Zhang, Qi (PetroChina)
This paper presents an uncertainty assessment project using Artificial Neural Network (ANN) for a giant multi-layered sandstone reservoir in Middle East, which contains several uncertainties and associated risks. Uncertainty quantification in history matching, production forecasting and optimization approaches often requires hundreds of thousands of forward flow simulations to explore the uncertain parameter space, causing forbidden computational time requirement, especially for large-scale reservoir models. In order to bypass this limitation, one can use a proxy to replace the time-consuming flow simulator. In this work, an optimized ANN is used as the proxy and an uncertainty assessment workflow is implemented for the giant Cretaceous multi-layered sandstone reservoir using a global optimizer. Using the ANN based uncertainty assessment framework, the impacts of the main uncertain parameters on production forecasting are assessed for this multi-layered sandstone reservoir. Then, field development optimization is also performed to optimize wells injection and production rates to maximize the economic measures considering uncertainties.
Yong, Li (Research Institute of Petroleum Exploration and Development) | Baozhu, Li (Research Institute of Petroleum Exploration and Development) | Benbiao, Song (Research Institute of Petroleum Exploration and Development) | Weimin, Zhang (Research Institute of Petroleum Exploration and Development) | Qi, Zhang (Research Institute of Petroleum Exploration and Development) | Xiong, Lihui (Research Institute of Petroleum Exploration and Development)
For the same reservoir geological model, different simulation models could be obtained through history match calibration by different engineers. In other words, there are certain uncertainties within the calibrated simulation models. So how to reduce the uncertainty during history matching is still a problem. This paper presents how to quantify the waterflooding uncertainty and reasonably forecast waterflooding performance through reservoir simulation for a large multi-layered sandstone reservoir in Middle East.
Based on the results of detailed geological characterization, dynamic description and parameter uncertainty analysis, three fine geological models are built, which stand for upside model, expected model and downside model. Then parameter sensitivity on waterflooding performance is conducted based on sector model simulation, and waterflooding development strategies are also optimized. The results are firstly applied for the three full field model calibration by reservoir history matching. After that the calibration models are used for waterflooding performance forecast and the performance uncertainty are also quantified.
Take a large multi-layered sandstone reservoir in Middle East as an example. The MU reservoir is still under primary depletion with only 5% recovery currently, and waterflooding is urgent. Firstly, sector models are used for parameter sensitivity analysis and development strategy optimization. Then based on parameter sensitivity analysis results, the three full-field model are all calibrated with good history match. And different model calibration need different parameter adjustment, such as downside model has stronger aquifer support than that of upside model and expected model because of the poorer connectivity. So different models show different characteristics, such as most of west-south flank of MU reservoir are flooded for Downside model, while only some local area and some zones are water flooded for Expected and Upside model. Then waterflooding performance of different development plans are forecasted and compared based on the optimum development strategies and calibrated models. Furthermore, the performance uncertainty are quantified based on the three models.
This paper offers a methodology and a case study of reservoir simulation history matching in order to reduce uncertainty and better waterflooding performance forecast for a large sandstone reservoir in Middle East. Comparison of the three models can help to better understand the reservoir. And the results are valuable for the following development options decision making. It also provides a reference for performance forecast and uncertainty analysis of similar reservoirs.
Li, Yong (Research Institute of Petroleum Exploration and Development, PetroChina) | Li, Baozhu (Research Institute of Petroleum Exploration and Development, PetroChina) | Liu, Lang (Research Institute of Petroleum Exploration and Development, PetroChina) | Xiong, Lihui (Research Institute of Petroleum Exploration and Development, PetroChina) | Luo, Hong (Research Institute of Petroleum Exploration and Development, PetroChina) | Peng, Hui (Research Institute of Petroleum Exploration and Development, PetroChina) | Wang, Daigang (Research Institute of Petroleum Exploration and Development, PetroChina)
Many oilfields in the world are mature and developed at the later stages of their life, and how to rehabilitate these fields is the biggest challenging problem. This paper presents an integrated approach with multi-disciplines to rejuvenate one of the world's super-giant oilfields in Middle East.
The K super-giant oilfield have more than 60 years' production history. Current oil recovery of the field is over 50% with more than 60% prolonged shut-in wells, and higher than 10% annual decline rate. The proposed integrated rejuvenation approach involved the analysis of comprehensive multi-disciplines, from geology and reservoir engineering understanding, to completion, stimulation, and surface facilities analysis. And based on the analysis results, shut-in wells are ranked into different types respectively, different treatments are applied according to well rank. Production rate of producing wells are optimized based on integrated models. New well candidates and other well work are also proposed.
For K oilfield, prolonged shut-in wells are classified into 4 ranks by principal component analysis, which mainly based on the understanding from bottom hole pressure evaluation, remaining oil description, offset well performance analysis, status of surface facilities, etc. Wells of rank 1 can be potentially open blowing directly with oil rate higher than 3000 mbd, and wells of rank 2 need install new ESP for artificial lift with oil rate only between 2000 mbd and 3000 mbd. While wells of rank 3 have much surface facilities problems and much lower potential oil rate, and wells of rank 4 have no potential to re-open. Also, an integrated model with subsurface, wellbore and surface facilities combined are established for production optimization. Based on the model, performance of producing wells can be analyzed, and flowing path or linkage pipeline of some wells were changed in order to meet the potential capacity of the well and surface facilities. Infilling well candidates are selected through pressure and remaining oil distribution analysis, which are mainly placed at the crest areas. Furthermore, other well works such as re-perforating, sidetracking, are also implemented with successful results.
This study details a successful application of an integrated field rejuvenation approach for a super-giant field, which stabilized the production of the field at the first year and made a 10% production rate increment for the second year. Most importantly, the methodology presented can be adopted in other similar mature fields.