A proper analysis and fluid characterization is an essential key for successful modeling the behaviour of gas condensate reservoir. This paper demonstrates a robust multiple equation of state (EOS) modeling process for gas condensate reservoir at Senoro field. Senoro is a new major gas condensate field in East Indonesia with estimated IGIP greater than 2 Tcf and CGR range from 3-80 STB/MMscf. Senoro field is divided into two structures: the northern part is a carbonate reefal build-up, namely Mentawa, member of Minahaki formation, and the southern part is a platform carbonate Minahaki formation. The hydrodynamic condition in both formations poses a challenge to fluid characterization, where Mentawa member has both oil and gas with active aquifer, while Minahaki formation only has gas bearing rock with aquifer. Senoro field has collected 36 samples, measured from down-hole and surface. The samples also cover composition analysis for surface recombined fluid. The required laboratory experiment such as CCE, DL and CVD have also been measured. The mathematical recombination was performed as a quality check to measure well-stream composition. Two EOS models have been developed successfully to determine physical properties and to predict the fluid behaviour of Senoro. The heptanes-plus fraction is split into three pseudo-components to characterize fluid using Gamma distribution model. The fine-tuned fluid properties from all available data match both EOS models satisfactorily. These EOS models have also been matched with historical single radial welltest model. Compositional grading has also been developed to generate compositional map. These established EOS models are used for compositional simulation. The gas and condensate profiles now could be predicted for optimizing field development plan. The use of EOS models can lead not only to a further field development strategy, but also to optimize the surface processing facilities.

As one of gas field producers located in South Sumatra Indonesia, the S field produced 70 MMSCFD as its peak production. It is a high pressure and high temperature gas impurities of 30% CO2 and 100-ppm H2S. The field has been producing since April 2010, with current recovery more than 50% of initial gas in place. Utilizing initial estimated OGIP (Original Gas In Place), the gas deliverability was predicted to last only until 2022. There are high uncertainties in estimating accurate reserves value due to lack of reservoir data such as reservoir pressure and SCAL (Special Core Analysis). Therefore, additional information such as SBHP (Static Bottom Hole Pressure) survey data and well optimization are essential to be conducted to narrow the uncertainties in reserves estimation and gas deliverability. Apparently, in 2018 and 2019 during CPP (Central Processing Plant) shut down for preventive maintenance activity, SBHP survey could be performed. Additional pressure data was utilized to update the OGIP analysis by combining several methods such as p/z analysis, flowing material balance, rate transient analysis and history matching of dynamic model analysis. The analysis shows conclusive result that there is significant increase in the OGIP and reserves, estimated 16% of additional gas reserves. To support enhance gas deliverability, the production network model was then created to evaluate existing production method. This updated system analysis showed significant bottleneck at the existing production system that limiting the production rate from the wells. As part of debottlenecking endeavor, temperature survey on the production system was employed to overcome the limited availability of pressure survey points in the system. Furthermore, the successful debottlenecking activity combined with temperature drop analysis resulted in 20% additional gas deliverability. This integrated evaluation and optimization also prolong the field lifetime until 2025. This paper describes some of the challenges and lessons learned during the evaluation and optimization in the high pressure and high temperature sour gas field.

Effective exploitation of the thin oil rim in the Gunung Kembang field is particularly challenging because of the huge size of the overlaying gas cap, and the thickness of the oil rim varying between 25 to 40 feet gross pay interval, not to mention the sizeable water aquifer underlying the reservoir. Horizontal wells were implemented since 1992 to enhance oil recovery by reducing gas and water coning, nevertheless, oil recovery still remain around 3%. As the pressure is depleting, horizontal wells revealed to pose higher risk than before, just like in the second stage of horizontal drilling in 2004, where water breakthrough and total loss occurred. The plan to add more horizontal wells to add recovery was coincided with POD commitment to deliver gas by gas cap blow down. This paper presents a team effort to formulate optimization strategy for maximizing oil recovery and revenue while delivering gas as committed in POD. Integrated reservoir characterization that comprises of carbonate depositional study, and reservoir simulation was conducted to best manage not only the drilling location but also number of wells and production strategy for next horizontal wells. Carbonate depositional study using existing logs and core data revealed the best oil potential zone in Baturaja formation in terms of porosity and permeability. Meanwhile, reservoir simulation grid was aligned with the zonation from carbonate deposition model, after that the performance of existing 10 wells was history-matched to develop an improved strategy. Sensitivity analysis conducted demonstrated that locating horizontal oil wells in the upper oil rim near the gas oil contact proved to be the best strategy for depletion of the oil rim. Among five scenarios developed, one final scenario was selected to accommodate both oil recovery optimization and gas cap blow down. This scenario includes eight additional horizontal oil wells while utilizing their produced gas to accommodate gas commitment, without drilling another gas well. Oil recovery is expected to rise to about 8% while gas is being delivered according to POD. Introduction Gunung Kembang Field is located in the South Sumatera Extension area of Medco E&P Indonesia working areas. This field was discovered in 1987 with GK-1 drilling and was put on production in June 1988. This carbonate reservoir has a thin oil column of around 40 ft sandwiched between thick gas cap of about 117 ft and water aquifer with the drive mechanism is mainly gas cap drive with weak water drive. Currently, cumulative production of this field has reached 3.8 MMSTB of oil and 50 BCF of gas with 10 wells, in which 6 of them are horizontal well. Because of apparent thin oil column, vertical well performance were upset by quick gas coning and water coning, thus encouraging the need for horizontal wells. Started in 1991, three horizontal wells were drilled; they are GK-7, GK-9 and GK-10. Excluding the production of GK-10 well which entered poor quality rock in the horizontal section, the cumulative production from other 2 horizontal wells until the end of 2004 is 2.5 MMSTB-indicating the success of horizontal well performance. Further simulation study was conducted by third party to maximize oil recovery in Gunung Kembang field by drilling 5 horizontal wells. Based on those simulation study, another horizontal drilling campaign was executed in 2004 by side-tracking 3 existing vertical wells, GK-1, GK-3, GK-6 to be GK-1 Horizontal Well (HW), GK-3 HW and GK-6 HW. Unfortunately, only GK-1 horizontal is considered successful, meanwhile the other two having problem in early water breakthrough, and total loss. Thus the oil recovery is still remains low at about 3% from total Original Oil in Place.

Well testing generates essential reservoir data, and although it can impact initial operating expenditures significantly in oil or gas upstream projects, the data generated can be essential to the efficiency of the completion operation ultimately designed. While having proven its value, data-gathering methods still must be balanced with operational and economic strategies, if the completion goals are to be economically feasible. Drill-Stem Test (DST) tools with downhole shut in and memory gauges are commonly used in well testing operations to provide reliable data and enhance operational efficiency of the completion. However, DST tools alone cannot monitor reservoir pressure response in real-time for justifying the subsequent operational objective changes during the data acquisition, because the recorded data cannot be retrieved at surface until the well test operation is completed, and the workstring is pulled out of hole. To overcome this problem, surface read-out (SRO) systems can be used with DST for retrieving downhole memory-gauge data in real time; thus, the pressure response can be monitored directly, and operational changes can be made immediately, based on actual reservoir conditions. An SRO system was used in Senoro-6 well to aid in justifying a shut-in duration to reach reservoir boundary and attain information that indicated the need for a stimulation treatment. Based on the real-time SRO data, it was found out that the permeability was lower than expected, and shut-in should be terminated earlier than planned, since the required shut-in time to reach boundary would be much longer than anticipated. Prolonging testing time would not be reasonable when reviewing operational and economic considerations. In addition, pressure transient analysis from real time SRO data indicated that the well had severe wellbore damage. Thus, the decision was made to conduct matrix acid stimulation based on the SRO data and to continue with post-stimulation well testing without pulling the DST string out of the hole. Post-test results showed a 22% production improvement, while the operation itself saved more than US$150,000 from daily rig cost. This approach in using the SRO system proved to be effective in helping to determine an efficient testing operation and completion strategy.

X field was discovered in 2001 and started producing in 2003. The formation is limestone supported with large aquifer. Main challenge is that wells must be produced with critical rate limitation, if a well is produced too hard, water coning and water breakthrough can occur, then oil production will disappear, as happened in one of X's well. In 2011, several wells were becomes ceased-to-flow due to an increase in watercut value, then pumping units were installed on these wells. However, due to recurrent mechanical downhole problems which limit effective production days, a new initiative is required to overcome these issues. After thorough analysis, ESP was chosen as best-fit artificial lift considering its versatility in deviated wells and high deliverability. In 2017, pilot phase of ESP implementation started in X-D4 well, which gave 150 BOPD average oil gain. Learning from the success of X-D4, comprehensive production strategy using ESP is considered crucial for optimum recovery. To support this strategy, an integrated optimization study with reservoir simulation model was used instead of analytical method to obtain more reliable production forecast. History matching was carried out from initial production data in 2003, a good match in liquid-oil-water-pressure data was successfully obtained, but poor match was occurred on gas production rate, this was ignored due to high uncertainty on gas measurements. The outcomes of simulation study were ESP well candidates, optimum production rate target and proper timing of ESP installation. The next step was the preparation of ESP which consists of the design and procurement of ESP. Following the ESP installation plan, it was also decided to increase power generation capacity at current surface facilities. Currently, 7 out of 10 ESPs have been installed. Power plant upgrading and overhead line installation to support ESP have also been carried out. The average oil gain obtained was 700 BOPD with cumulative of 160 MBO (from 2017 – until 2018). This optimization case will contribute 1.5 MMBO additional reserve from "do nothing" case. Economic evaluation shows a very good viability with significant additional gross revenue. This optimization project has succeeded in reducing oil deferment from ceased-to-flow wells and extending the field's life. Good collaboration between each part (subsurface and surface) in this project has succeeded in producing significant oil gains. Continuous monitoring is still needed to further match optimization forecast with actual conditions. Long-term plans, some improvements are still needed in the reservoir model, one of which is OOIP value, there is a possibility that the actual X OOIP is bigger than the one in the reservoir model.