Conventional gas flooding suffers from poor sweep efficiency in heterogeneous reservoirs. In absence of mobility control, gas preferentially travels through the path of least resistance, bypassing oil in low permeability areas. Stable foams restrict flow in high permeability channels, diverting flow to the lower permeability layers. This allows injected fluid to contact oil which would have been unswept by conventional gas flood. The objective of this research is to determine the extent of improvement caused by use of foam for CO2 floods in a range of heterogeneous reservoirs. Moreover, this study aims to provide a qualitative understanding of foam in heterogeneous reservoirs which would help in designing successful CO2 foam flooding in enhanced oil recovery projects. The simulation study involves 2D reservoir models with varying reservoir heterogeneity modeled by different Dykstra-Parsons coefficients and correlation lengths in the areal and vertical directions. A Surfactant-Alternating-Gas (SAG) scheme and a Water-Alternating-Gas (WAG) scheme were carried out to determine
Production Enhancement (PE) opportunities in a 30 years-old Field D in Balingian province, offshore of Sarawak, Malaysia are dwindling. Behind casing opportunities (BCO) in relation to bypassed pay with good reservoir properties are either already perforated and produced or too costly and complex to be executed due to well issues. An in-house evaluation tool, Resolution Enhanced Modelling (REM), was developed by PETRONAS Petrophysics Department to evaluate and characterize thin beds or laminations. These Low-Resistivity-Low-Contrast (LRLC) sands are commonly bypassed as conventional logging tools cannot resolve their true parametric values and the apparent log responses across these zones appeared as shaly sand. By running REM across these intervals, the properties of the thin sands can be properly characterized, improving the net pay and economics of perforating and producing these reservoirs. In addition, a Rock Type (RT) based technique was used to evaluate some LRLC candidates in Field D. REM was run on LRLC sections in idle wells to evaluate their potential. To derisk and test the methodology, Well A3 with relatively more promising results was chosen as the first well to be perforated. Moreover, both strings of Well A3 were idle which makes it operationally easier to carry out the perforation job. From the initial analysis, the LRLC intervals in Well A3 could contribute to additional reserves of 0.3 MMstb with start rate of 300 bopd. The job required usage of barge assisted coiled tubing to pump cement and shut off existing high watercut zone and slickline to perforate through tubing. The actual job duration was prolonged from 30 days to 50 days due to monsoon season, driving the cost up to twice the planned amount. Post perforation, the initial oil rate was tested to be 500 bopd. After increasing the choke size, the well could flow at 800 bopd. Convinced by the success of Well A3, the same methodology was applied to Well C8 located at the north side of the field. Well C8 encountered operational difficulties such as lower than expected top of cement and perforation gun malfunction, resulting in only 54% of the proposed depth being perforated. Well C8 produced high gas, with initial well test rate of 10 bopd. Managing a brownfield where the easy oil is mostly exhausted can be challenging. Therefore, the team has to be more creative in unlocking the remaining oil and prolonging the life of a well. By using REM, the overlooked potentials hidden in LRLC sands can be accurately estimated, making the economics to perforate them more attractive to pursue.
Smart field accessories are already widely used in the industry. Donkey field is ready to jump on the bandwagon by installing 8 wells with these accessories. In addition, Donkey field is equipped with data transmission system or we called it Integrated Operation (IO) where the data is transmitted directly to shore for faster decision making and continuous data monitoring. For every installation for these jewelries, the question is always why do we need these? Most of the time, well inaccessible is the drive of their installation. But, the benefit of this jewelries are beyond that. For example, optimization for commingle is easier for this installation. With Inflow Control Valve (ICV), it is easier to control its injection for each layer. IO helped the engineer to dive deep into well and reservoir performance or problem. This technology helps the engineer to have full picture on field potential. So, where is the problem? "Smart well" have a good ring to our ear which make us forget what is the challenges underlying its installation. After 2 years of its installation, almost all these jewelries began to shows their problem. Team face quite a challenge to rectify this problem especially on well jewelries. Because of the location of the field, transmitters’ signals are really impacted by the weather. With the tropical climate of Donkey field, the data missing for interpretation is quite massive. Hence, it is difficult to get good data for it. During initial design stage, everyone need to consider the configuration and location of the field before we start to consider these expensive jewelries. Do we really need it? And are we ready for its maintenance, not just on its installation? How frequent is its maintenance? All of these need to be considered before we jump on the bandwagon.
Water injection was implemented in a 30-year old brownfield offshore Sarawak, Malaysia in August 2016. Seawater is processed at a Water Injection Facility (WIF) and sent to four injectors, each injecting commingled into two or three different reservoirs. This paper discusses on challenges faced in initial start-up of water injection in a brownfield including the inability to meet target injection rate, frequent WIF trips and off-spec injection water, metering issues, as well as mitigation measures and lessons learned. Initially, the injectors were able to take in only 33% of target injection volume as per the FDP plan. To remedy this, a ramp-up injection procedure was introduced to allow the injectors to gradually take in more water until the target injection rate could be achieved. A leaner and practical water quality SOP was devised to reduce injector downtime, particularly for satellite platforms, while ensuring water quality is not compromised. Injection fall-off testing was performed on the injectors to investigate the root cause of the injectivity issue through manipulation of downhole ICV. Through this exercise, it was discovered that the injection meters were not properly calibrated. A combination of these methods proved successful in improving injection rate of the water injectors. Initial SOP developed for the injection water quality required testing of water quality at each sampling point including at unmanned satellite platforms, prior to recommencement of water injection post WIF shutdown. This is despite the duration of shutdown being shorter than the frequency of required sampling, which led to prolonged injection downtime. The requirement for water sampling for satellite platforms were modified to be less stringent while still maintaining good water quality. As a result, there was an improvement in WIF uptime from 92% in second month of injection to 99% in the fifth month. The fall-off testing provided valuable information in terms of well and reservoir data. Careful and specific operational steps were required to adjust the downhole ICVs during fall-off testing, as opposed to hard shut-in of the water injectors which would cause backpressure and tripping of the WIF. Adjustment of the surface-controlled ICVs allowed sequential testing of different zones, which successfully shortened the total testing duration by 25%. The fall-off test also revealed that an injector was injecting into a reservoir which did not benefit any producers, and that the flowmeters for certain injectors were not calibrated properly. Through these efforts, injection rates were successfully increased by 25 kbwpd, from 35% to 75% of the total injection target, within six months of its implementation. Water injection start-up challenges and mitigation methods are not often discussed in literature, such as adjustments needed to achieve target injection rate, operational steps in well testing for commingled injectors, and finding the optimum balance between quality and practicality of injected water testing. It is hoped that the issues and strategy in this field will serve as lessons learnt for upcoming water injection projects in this and nearby fields.
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