Sand face completions have a major impact on a well's deliverability, by determining its productivity or injectvity throughout its expected life. In the Niger Delta, most reservoirs are shallow (below 10,000 ftss) and poorly consolidated, sand control forms an important part of sand face completion design. Sand management strategy involves using a software FIST (Fully Integrated Sand Prediction Tool) to carry out sand failure prediction analysis. In cases where sand failure is imminent, a sand control selection guide is used to determine the optimal sand control method to be installed. The selection is benchmarked against the performance of existing sand controls designs in analogue wells the in the region. A number of sand control mechanisms have been successfully deployed in various completions across Niger Delta which includes Chemical Sand Consolidation, Gravel Packs (Internal/External), Slotted liners, Expandable Sand Screens (ESS), etc. The complexity of deployment varies widely from the most complex multiple IGP/EGP to slotted liners. In all, most of the methods have exhibited good sand control properties however, with varied productivity. The ESS has presented a good balance between ease of deployment, productivity and life cycle management of the well. A field in the greater Gbaran area of the Niger Delta is proposed to be developed by three gas wells targeting three reservoirs. The reservoirs are unconsolidated and below 10,000 ftss, with Sonic log transit times in the range of 93 - 162 μsec/ft. Sand failure prediction on these three reservoirs using FIST indicated a high failure probability (95 – 100%) during the production life, thus requiring sand control. Following the process of selection, and Cased-Hole ESS was proposed. Although cheaper and easier to install with better productivity, a proper evaluation of the erosion tendency especially in Cased-Hole application of ESS in gas wells is essential to ensure full life cycle coverage. This paper documents the results of the evaluations carried out, optimization methods employed to evaluate the proposed sand control mechanism.
The need for the estimation or evaluation Original Oil Water Contact (OOWC) prior to reservoir development is very pertinent to appropriate well placement within a reservoir. Oil and gas water contacts are determined via various sources including but not limited to Petrophysical logs, RCI data, Reservoir Simulation, Fault Seal Analysis (FSA), Quantitative Interpretation and Hydrocarbon Column Analogues. This paper focuses on an integrated approach of predicting OOWC using some of the methodologies highlighted above. The study explores the feasibility of further oil development in the Yoko field to grow production and increase reservoir ultimate recovery. Three wells have been drilled so far in the field and none encountered OOWC. Three (3) key reservoirs account for about 69% of the total field hydrocarbon resource but with significant uncertainty in fluid contacts column (about 132ft) and wide static and recoverable volume range. An effective and commercially viable field development plan is premised on the reduction of contact uncertainty. Inorder to narrow the contact uncertianty, a multidisciplinary approach has been used and they include (a) Petrophysical Logs (b) Analogue oil column studies from adjacent fields (c) Fault Seal Analysis (FSA) to determine maximum column in the reservoir (d) Quantitative Interpretation (QI) and (e) Dynamic simulation. The analogue oil column from neighbouring field was used to benchmark the possible oil column for Yoko field. FSA which relies on the sealing capacity of the faults due to the amount of mechanical mixing from fault throws was also considered. The upper and lower limits of the fluid contacts were estimated from acoustic impedance amplitude plotted against depth. The reservoir dynamic models was also history-matched (7 years of production history) to calibrate and ascertain the limits of the possible contacts for the reservoirs. The result of the evaluation is a significantly reduced volumetric uncertainty range. In one of the reservoir, there was a progressive reduction in fluid column uncertainty from 132 ft to 11 ft. In general 55 – 92% reduction of the initial uncertainty was achieved. This reduced range enabled a commercially viable Development Plan for the field.
Uncertainty management for resource volume of a brown field is relevant. An analytical approach via dynamic model was used to evaluate this impact on a developed gas reservoir (brown) by two other reservoirs. One of them is a green oil-rim reservoir, while the other is a developed oil reservoir. This is due to sand-to-sand juxtaposition with the two reservoirs. Integration of available data over time, while considering all the reservoir uncertainties was adopted. This was buttressed by the continuous production from the gas reservoir, that had already gone past the initially evaluated Gas Initially in Place (GIIP). The brown reservoir is a highly faulted gas reservoir with twenty-seven (27) years production history, by seven wells. The reservoir's GIIP re-evaluation had been done twice over the years. This was because it had fully developed its ultimate recovery, with three wells still producing. This GIIP re-evaluation approach could no longer be utilized, as it had very good well coverage. Fault seal analysis, pressure, PVT sample and log data taken over time reveal the likelihood of communication across the stacked reservoirs. A multi-tank material balance model (MBAL) was built via a multidisciplinary approach. The model was history matched using an experimental design approach that saved time and contacts were calibrated. The result showed the quantity of hydrocarbon in both reservoirs that have flowed into the developed gas reservoir. This provides a snapshot on the resource volume impact of the reservoirs with respect to their development and uncertainty management. Revised development plans and resource booking for the reservoirs are also study outcomes. This is relevant for business decisions on resource volume booking and reservoir management. This approach is a quick win within the Well, Reservoir and Facility Management (WRFM) workspace. Further work by building a 3D simulation model and pressure data acquisition is required for robust benchmarking.
Clearly delineating contacts are usually aimed at before development, but what happens when later data indicates contacts different from what have been interpreted? How do we ‘work back in time’ to re-estimate the original contacts? Our case study documents a reservoir which due to the poor well coverage, paucity of log data, side wall sample and pressure data, was initially interpreted as an oil bearing reservoir, however, a new well drilled post production of over 20 years indicated the presence of a huge gas cap, the size of which could not have been due to the formation of a secondary gas cap. This necessitated the determination of the original contacts in order to properly define the reservoir volumes which will impact on its future development. This paper presents the use of an integrated thinking approach which makes use of all the available geological, petrophysical and dynamic data in determining the original fluid contacts in a post production scenario. Reservoir simulation using simple tools as material balance combined with petrophysical and geological concepts were applied in this paper. The results obtained shows that the use of static data alone such as petrophysical logs in determining the original contacts for post production reservoirs can be greatly misleading as the results obtained may conflict with dynamic data available for the reservoir and therefore not fully representative of the reservoir and its history.
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.