|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Value Creation can be achieved through FDP optimisation initiative for offshore fields that have been impacted by recent slump in activities and investments in the Oil and Gas industry. Each stage of the FDP process can be reviewed and respective value and cost target be revised. It is to ensure that process for the opportunity still carry business value, and aligned with business objectives at current industry outlook. Alongside the opportunity maturation process, there should also be emphasis on value assurance to maximise value and chance of success.
Offshore development of a green field gas development in Peninsular Malaysia was a successful story of Integration and engagement of various functions and disciplines throughout the FDP optimisation efforts, by keeping the FDP stages as "live" cycles. It let the optimisation process to encompass all activity spectrum from subsurface to surface, and warranted the project to be fully assessed from uncertainties and risk management to optimising the value of the project.
Early determination and understanding of the objectives and area of focus for maximum impact on value creation initiatives were chosen to be the road map. Moreover, collaboration between the teams to revise drilling, completion and the depletion strategies with capital cost phasing were identified to be key areas for a successful development and cost optimisation of the project. Drilling and completion strategies for the wells selected in a manner that they focused on most productive zones at the beginning, with development of the shallower reservoirs by workover and intervention activities upon depletion and pressure equalisation with the lower zones. The strategy also led the capital cost to be classified as operational as future expense without compromising the reserve to be developed.
The result of the work led to a significant cost saving which in turn allowed execution of the project from preservation to drilling stage in almost 6 months.
This paper will highlight the initiatives and activities that made the project to be successfully move from preservation to execution mode.
Sabzabadi, Ali (Petronas) | Masoudi, Rahim (Petronas) | Arsanti, Dian (Petronas) | Aslanyan, Irina (TGT Oilfield Services) | Garnyshev, Marat (TGT Oilfield Services) | Minakhmetova, Roza (TGT Oilfield Services) | Karantharath, R. (TGT Oilfield Services) | Aslanyan, Artur (Nafta College) | Farakhova, Rushaniya (Sofoil) | Gulyaev, Danila (Sofoil)
The paper describes a practical case of using multi-well pressure Pulse-Code Testing (PCT) for assessment of inter-well connectivity and potential reserves for placement of new wells in offshore environment. The study was based around two PCT cells (one calibration and one scanning) which were surveyed on the same platform within one month. The calibration PCT cell was set around injectors in peripheral area to eliminate the uncertainty in reservoir saturation, and provided estimation of macroscopic reservoir permeability (k a) and macroscopic rock compressibility (c r) in cross-well intervals. The reservoir permeability was found to be in good correlation with core-calibrated log prediction, while rock compressibility turned out to be twice higher than expected. Additionally, the calibration PCT cell picked the seismic fault as being impermeable and provided accurate values of its proximity to the pulsing well and its extension in the north direction.
Chemical EOR is one of the promising methods to improve the oil recovery. However, due to high cost of the process, there are challenges to minimize the cost and maximize the oil recovery. Some influencing parameters should be taken into account in a systematic approach to find their impact on oil recovery and accordingly optimizing the process.
In this study, we present a robust optimization workflow of alkaline-surfactant (AS) flooding into a thin clastic reservoir of a field in the Malay Basin. There are coreflood experiments and pilot tests on this field that can be quite helpful to provide a basis to find out the appropriate range of input parameters. Optimization work is based on response surface methodology (RSM) and particle swarm optimization (PSO) technique that aid us to indicate the optimum oil recovery from chemical flooding. In order to get the utmost advantage of this workflow, the waterflooding should be optimized prior to the chemical flooding optimization to maximize the sweep efficiency and oil recovery from the chemical flood.
Evaluation of coreflood and pilot tests indicated that some parameters need supplementary evaluation to investigate their effect on reservoir performance and flow dynamics. These parameters include residual oil reduction by chemical, relative permeability curves, chemicals adsorption, chemical concentration, slug size, injection rate, and initiation time of chemical injection. Based on the result of tornado chart, residual oil reduction and injection rate exhibited highest and lowest impact on oil recovery. RSM was used to explore the relationship between input variables and objective function. Some design parameters such as chemical concentration, slug size and initiation time were examined in this stage. Afterwards, proxy models have been built using polynomial regression and neural network methods. The results showed that the proxy model by neural network method revealed better performance for prediction of the simulation results. The proxy model was used to calculate the oil recovery for any combination of input parameters. Besides, it was used to assess the parameter sensitivity and identify the impact of any input parameter on oil recovery. At the next stage, PSO method was utilized to optimize the oil recovery by chemical flooding. It was found that the optimized water injection rate and pattern for water flooding scenario need further optimization to improve the sweep efficiency and thereby oil recovery by AS flooding at later stage. Running numerous simulation cases is normally expected to optimize the process by conventional methods and the proposed PSO approach can be used to reduce the number of runs significantly. Sensitivity analysis provided a very good understanding about reserve ranges for the different influential parameters. Optimizing the cost of chemical flooding and improving oil recovery are other outcomes of this study.
Angsi field is slated to be the first in the world for Alkaline-Surfactant and Polymer (ASP) chemical flooding via a floating structure in an offshore environment. The chemical flooding will be for 3 years with 6 months of low salinity water pre-flush injection prior to chemical injection to condition the reservoir, and 6 months of treated seawater with polymer injection as post-flush activity. The chemical flooding will be conducted via injection of treated and partially desalinated seawater mixed with ASP chemicals produced from the floater which is tie-in to the existing Angsi water injection pipeline network (Figure 1.0). Angsi reservoirs will experience three (3) different salinity range exposures with two (2) as invading fluids with effects of chemical cocktail, wettability and fluid distribution. One of the main challenges for ASP flooding in an offshore environment is handling the chemical residuals breakthrough in produced water causing the water unable to be disposed overboard. To overcome this problem and to eliminate environmental pollution, a full scale Produced Water Re-Injection (PWRI) system with full integration to existing Angsi Produced Water Treatment (PWT) system should be adopted to meet the new water reinjection specifications. Since the PWRI water will be commingled with treated and partially desalinated seawater mixed with ASP chemicals from the floater, it is paramount to predict the range of salinity of the produced water over time to help to design the PWRI and Floater's water treatment system to achieve the final water quality and optimum salinity required for an effective ASP cocktail for re-injection. This paper will summarise the PWRI design and operation philosophy coupled with subsurface studies to predict salinity profiles for the produced water.