This paper presents an application of integrated asset modeling (IAM) to a rich gas condensate field under recycling mode located in Abu Dhabi. The field is composed of many non communicating gas reservoir units; some of these units are already developed and being produced for a number of years, while some others reservoirs are in the exploration / evaluation phase. Potentially, some of the reservoir units are sharing or will share the surface network and the process facilities. The project consists of developing a platform for a solution that can respond to the current requirement of the available modeled reservoirs; at the same time, the solution should be expandable to account for the reservoirs being explored or at early production phase. The first step of the study was to construct the surface network for both gas injectors and gas producers. The subsurface compositional simulation models for the developed reservoirs were available and history matched. The platform linking the surface to subsurface was developed and set to fulfill the field development requirements. The solution was validated for the historical performances, measurement of the surface network were collected and validated in the stand-alone mode and in the coupling mode. Tests for the prediction performances were also performed, and led to more realistic profile showing the recoverable reserves for recycling and blowdown considered scenarios. The integrated model indicated area of improvement in pressure history match of the field simulation model for few wells where it was not easy to observe in standalone simulations. The platform for the integrated Asset modeling is expandable to further development that could be plugged-in, either functional adds-on like process modeling and economic evaluation or organic like adding additional wells to the existing models or adding new models for exploration unit. It will be also applicable to see the compression requirements during any time in the future.
This work presents a case study of developing the transition zone for a giant oil reservoir with significant gas cap and water aquifer, in Abu Dhabi-UAE, addressing geological and dynamic aspects, field development approach and present status. The reservoir lies within a relatively low relief heterogeneous carbonate structural trap and characterized by lateral and vertical variations in reservoir rock and fluid properties. Given the relatively low permeability of the mentioned reservoir, the transition zone contains a significant STOIIP; which called for this challenging development. A number of parameters were addressed and optimized as part of the transition zone development plan. The dynamic modeling suggests that a full field ultimate recovery of 70% can be achieved by developing the transition zone. However, considering the complexity of the reservoir, thickness of the transition zone and current market conditions, the field development would be economically viable for a period of 50 years under miscible hydrocarbon WAG, provided the most effective development strategy in terms of the definition of transition zone, optimization of the number, location, orientation and horizontal reach of the proposed wells. Various development strategies for the transition zone were investigated during the study considering all possible uncertainties and economic drivers, all of which are discussed in details in this paper. 12 years of early production scheme (EPS, 1993 to 2005) and 12 years of phase-I development helped better understand the reservoir and characterize the transition zone. Total of +150 wells penetrated the reservoir with good data gathering (ROS, Core, SCAL, PVT, MDTs…etc.). PVT studies indicate a wide range of compositional variation areal and vertical, which further complicates the development plan considering the surrounding sensitive environment. The transition zone is defined by rock types and the corresponding critical saturation. The amount of recoverable oil in the transition zone is depending on the distribution of oil saturation as a function of depth and the relationship between initial and residual oil saturation in the transition zone. The reservoir is under EOR (Miscible HC GI at crest and WAG at flank) since commissioning of phase-I in 2005 and tracers were injected in 2012; adding challenges to the history matching and tracking of the flood front. Given the limitation on surface handling capacity of the current facilities, the transition zone development called for well placement in the upper part of the transition zone using 6 months WAG cycles. The first well of the transition zone development has been drilled; which has positively validated the definition of the transition zone, built confidence on the subsurface modeling approach and commended the planning strategy.
Carbonate reservoirs introduce challenge in providing accurate water saturation from conventional Archie equation. One of the reasons is due to the variability of the Archie cementation factor "m" because of complex and tortuous nature of these heterogeneous carbonates. The study was performed by integrating core and log data from advance measurements to understand the root cause and range of the variability and an attempt to link sedimentology and diagenetic facies to petrophysical groups. The Study focused on a carbonate reservoir with complex pore network. The formation resistivity factor (FRF) measurements were conducted with high-resolution sampling on a selected well. Each of FRF plug has associated porosity, permeability, thin sections, MICP, NMR and high-resolution dual energy micro CT scan. The m value from FRF is then plotted along the porosity-permeability plot. The capillary pressure parameters (entry pressure, slope, inflexion points) were extracted from MICP and relationship is plotted against m. Diagenetic facies described from the thin sections is compared versus m. Principal component analyses was conducted to identify factors relating to m. The uncertainty on water saturation associated to variable parameter m was assessed using Monte Carlo analysis on multiple wells. An advanced multi-frequency dielectric logging tool was run on couple of wells to provide variable water-phase tortuosity (MN) measurement. Specific analysis was performed to extract the variable m value from the measurement over limited zones, which has been derived from core "m" measurements. Several wells located on the flank of the reservoir below water level were evaluated. Dean stark measurements were performed on a well and used to validate the saturation calculation. It is obvious that the evaluated reservoir has high degree of heterogeneity as indicated by complex pore network with multi modal pore system as shown by the thin sections, MICP and plug CT Scan.
Assessing CO2 EOR in different areas of a field with different rock and fluid properties requires proper dynamic reservoir modelling. Good SCAL data is a key input to the dynamic model. Consequently a comprehensive SCAL program was designed for a super giant carbonate reservoir, onshore Abu Dhabi, for modeling CO2 EOR process in secondary & tertiary conditions. A careful selection of the core material based on a Petrophysical Group (PG) review was performed to make the experiments representative of key areas of the field in which CO2 flood is planned or studied.Laboratory experiments were designed at full reservoir conditions with H2S oil bearing, and to assess possible impact of H2S on displacement efficiency. Water-oil relative permeability tests showed insignificant impact of H2S, compared with non-H2S tests on cores of different PG's. Injectivity issues and importance of brine composition on water mobility were identified. Trapped gas to water and oil were also mapped successfully.The comparative analysis of CO2 EOR flooding scenarios using long composite cores with continuous CO2 injection and CO2 WAG were also performed. They indicate higher displacement efficiency with continuous CO2 injection. Tests were also conducted on composites with non-H2S live crude, representative of reservoir zones with little or insignificant presence of H2S.This study indicated for the first time in the published literature, the impact of H2S in water-oil relative permeabilities of carbonates at full reservoir conditions. The gas process displacement efficiency tests also verified negligible impact of H2S (up to 12%) in CO2 EOR 1D core floods.
Facies model is the basis of the geological model and determines the overall reservoir appearance. Due to limited data and extremely strong heterogeneity, the distribution of superior reservoir was hard to predict in a carbonate reservoir in the UAE, which often leads to empty wells and severe economic losses. With the help of neural network, a systematic study of sedimentation and diagenesis was carried out. The main controlling factors of reservoir properties were identified, and rock types were defined. Based on this, the facies model was established. The paper proposed a facies modeling method based on comprehensive sedimentary and diagenesis study assisted by neuro network. Firstly, sedimentary facies study was conducted to clarify the sedimentary background and reservoir geological architecture. Then, the diagenesis study was performed. In general, the main controlling factors for superior reservoir were deposition and cementation. Thirdly, rock type definition was established based on the knowledge of deposition, cementation and MICP data. Fourthly, the logs were processed, including quality control, normalization, etc. Then the sedimentary, diagenesis and rock type interpretation for the limited cored wells were propagated to the uncored wells using the neural network IPSOM method. The trend of deposition, cementation and rock type distribution were depicted. Finally, the rock type distribution was studied based on the trend of deposition and cementation, then the facies model was established. The study area was mainly proximal carbonate sedimentary environment, including the subtidal inner ramp and intertidal tidal flat. Diagenesis mainly included compaction, cementation, dissolution, and dolomitization. For the main reservoir, which was mainly the inner ramp deposits, SRT1 and SRT3 were defined as grain-dominated deposits with weak-medium cementation and medium-strong cementation, respectively. SRT5 was non-reservoir. For the secondary reservoir, it was intertidal environment, and mainly micrite dominated deposits. It only forms reservoir with dolomitization. SRT2 was defined as dolomitized micrite dominated deposits with medium-strong cementation, and the reservoir properties had been greatly improved. SRT4 was defined as weak-medium dolomitized micrite dominated deposits with strong cementation, with limited improvement in reservoir properties. SRT5 in this sedimentary environment was also defined as non-reservoir. With the neural network IPSOM method, the interpretation of deposition, cementation and rock type for the cored wells were propagated to non-cored wells and the trends were depicted. Then the rock type trend was finalized. Based on this, the facies model was established, and the cause of the dry wells was well explained. For this highly heterogeneous reservoir, the core analysis data was very limited. The cores were studied in detail, then the understandings were propagated to the uncored wells, which greatly enhanced the database. Based on this, a sedimentary facies model is established, which characterizes the distribution of high-quality reservoirs and provides a solid basis for oilfield development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.