Kenali Asam field, Pertamina EP working area, is located in West Sumatra of Indonesia. The field was discovered by NIAM in 1929. There are 285 wells were drilled which consist of 99 producing wells, 20 injector wells, and 8 dry well wells, and the rest are suspended wells. The reservoirs are layered reservoirs from shallow to deep zone, and 16 production zones. The oil was produced from primary stage to secondary stage. The secondary stage has been started by injecting water since March 1993. The water was injected to specific layer such as B/650, F/730, N/990, and S/1170. The peak production of primary recovery was 13,643 BOPD with water cut 14.4% in September 1954. Peak production of secondary recovery was 2105 BOPD with water cut 50% in October 1994.
Pertamina's EOR department and Business Unit of Jambi field conducted pilot project to the zone of P/1050 with line drive pattern flood. The line drive pattern consist of 4 injection wells and 4 production wells. The pilot plan purposes are to evaluate the effect injection in that area to increase the energy of the reservoir, to sweep the oil to enhance the oil production. Before the water flood was commencing, chemical tracer was conducted to check the connectivity among the producers and injectors.
The chemical tracer IWT-2000 was injected to the KAS 63 (east area) for amount of 26 liters on November 17, 2007. The chemical tracer will be expected to flow to the monitor wells (KAS 227, KAS-028, KAS-164, KAS-39). Monitor wells are also considered as producer wells. The chemical tracers was detected in the monitor well (KA 39) after four months of injection from KAS 63. The rest of the monitor wells were not detected at all after 284 days of injections. But the connectivity analysis of injection and production showed that gross production, fluid level and bottom hole pressure increased in production wells.
In the west area, the chemical tracer IWT-1700 was injected to the injector KAS-73 in the mouth of 61 liter. The monitors wells, as well production wells, are KAS 35, KAS 38, KAS 243. The chemical tracer was detected in 3 months after injections in KAS 35. But there is no chemical detection in well KAS 38 and KAS 243 after 283 days. But, from the production analysis shows similar phenomena as in the east area. KAS 38 and KAS 243 showed the increment of gross production, pressure, and fluid level in the wellbore.
The waterflood pilot of layer P/1050 in Jambi area already conducted for couple years and the cumulative oil produced is more than 22 MBBO. This paper will described and evaluate the difference respond of fluid injection using chemical tracers and water. In the chemical tracer, it was detected the chemical concentration to evaluate the connectivity. Based on the water injection, it was evaluated the production performance to see the incremental of gross production, pressure and fluid level in the production performance.
Historically, in the Melibur oil field in Sumatra, Indonesia, typically more than two squeeze-cement jobs are required before cement isolation is achieved. Eventhough the goal for water-zone shut-off is eventually achieved, we tie-up staff and equipment an the cost per water-shut-off is high.
This circumtance challenged us to try a different squeeze cementing technique in order to achieve water-shut-off after one squeeze cementing job.
We considered various different approaches, such as modifying the cement recipe, injecting waterconformance chemicals and a surfactant soak.
Fluid-compatibility tests were performed, where various chemicals were added to a mixture of formation oil and water, to see which chemicals were most effective to de-emulsify the oil-water mixture. The idea was that cement would better bond with the formation water if it were separated from the formation oil.
Knowing the wetting characteristics of the reservoir rock is a must before deciding to use surfactant. The chosen surfactant must be water-wet and be non-damaging to the formation. We found an anionic surfactant was best for our formation.
Next came the hardest part, deciding the concentration of surfactant. In the lab, we increased the surfactant concentration gradually from 0.5% to 4% to see the effect on the cement bond. We found that if the surfactant concentration was too high, then the setting of the cement was retarded, and the additional waiting time was unacceptable for the field operation. We found that a 3 % surfactant with a 12-hour soak in the reservoir was best.
An additional benefit of the surfactant was it changed the oil-wet rock into water-wet rock, and thereby mobilized oil that was trapped near the rock surface. This made it easier for cement to bond with the formation.
Finding the optimal location of non-conventional wells increases significantly the project's Net Present Value (NPV). This problem is nowadays one of the most challenging problems in oil and gas fields development. When dealing with complex reservoir geology and high reservoir heterogeneities, stochastic optimization methods are the most suitable approaches for optimal well placement. However, these methods require in general a considerable computational effort (in terms of number of reservoir simulations, which are CPU time demanding).
This paper presents the use of the CMA-ES (Covariance Matrix Adaptation - Evolution Strategy) optimizer, which is recognized as one of the most powerful derivative free optimizers, to optimize well locations and trajectories. A local regression based meta-model is incorporated into the optimization process in order to reduce the computational cost. The objective function (e.g., the NPV) can usually be split into local components referring to each of the wells: it depends in general on a smaller number of principal parameters, and thus can be modeled as a partially separable function. In this paper, we propose to exploit the partial separability of the objective function into CMA-ES coupled with meta-models, by building partially separated meta-models. Thus, different meta-models are built for each well or set of wells, which results in a more accurate modeling.
An example is presented. Results show that taking advantage of the partial separability of the objective function leads to a significant decrease in the number of reservoir simulations needed to find the "optimal" well configuration, given a restricted budget of reservoir simulations. This approach is practical and promising when dealing with a large number of wells to be located.
In view of characteristics of low permeability sandstone reservoir and the aim of water control and oil increment, a mild water control technology referring to the alternative injection of anionic and cationic polymer for in-depth profile control in low permeability sandstone reservoir was proposed and developed when the oil wells were in high water cut stage. The adsorption equilibrium mass concentration of the cationic polymer is 1500 mg/l and the adsorption equilibrium time is about 8 hours, while the adsorption equilibrium mass concentration of the anionic polymer is 1000 mg/l and the adsorption equilibrium time is about 6 hours. The physical simulation experiment shows that anionic and cationic polymers alternative injection and prior injection of cationic polymer with high plugging capacity are better than the single polymer injection. The plugging capacity increases with the increase of injection rounds, the optimized injection round is no more than 3 times according to economic benefit. This technology is successfully applied in Shuangqian 6 well of Henan oilfield in June 2010. After treatment, the high permeability channel is effectively controlled, the water cut obviously decreased and the oil production increased, it is shown that this technology is a reliable and feasible technology and worthy to be widely applied in low permeability sandstone reservoir.
Over the last decade, an industry wide shift to unconventional plays has occurred due to advances in technology allowing for the recovery of previously uneconomic reserves. The primary objective of completions in these unconventional reservoirs is to increase the effective surface area of the well to maximize reservoir contact. Horizontal drilling and multi-stage fracturing are two technologies which have accomplished this. The two main methods of horizontal, multi-stage completions currently used in unconventional reservoirs are: cemented liner "plug and perf" and open hole, multi-stage fracturing systems.
This paper provides an introduction to unconventional reservoirs, describes the main methods of horizontal, multistage completions, and discusses how the choice of method can affect good fracturing practices as well as long-term production. Case study examples are presented from a variety of unconventional reservoirs included including shale, tight sandstone and carbonate formations.
Operators working in a number of unconventional reservoirs, such as shales and other tight rock formations are experiencing faster than expected production decline rates, resulting in reduced long-term, ultimate recovery. This may be in part due to the abandonment of good fracturing practices, developed over the past 50 years, with the advent of horizontal, multi-stage fracturing. Issues such as near wellbore conductivity, flowback, and fracture tortuosity that can have a significant effect on the long-term production of wells need to be considered when choosing a completion method, particularly for unconventional reservoirs.
Unconventional plays are becoming a significant part of the oil industry today and will become a bigger part in the future. It is important that the reservoirs are completed optimally to make them as productive as they can be. The information provided in this paper is applicable to unconventional resource plays worldwide.
Intelligent well technology is a relatively new technology that has been adopted by many operators in recent years to improve oil and gas production, and recovery. The technology uses downhole monitoring and control to regulate flow condition and provides solutions to production problems. It is one of the most effective means for optimization of commingled multilateral wells in heterogeneous reservoirs. Due to the high cost and complexity in intelligent multilateral well constructions, accurate modeling of the reservoir, completion and wellbore performance is essential to design an economically beneficial well, and the critical component, inflow control valves (ICV), should be integrated into the performance modeling process.
This paper presents an integrated analytical model that is built on existing models for predicting reservoir and wellbore flow behavior. Also, equations that can predict the flow performance through restrictions such as ICVs, in a multilateral well system are incorporated into the analytical model. The integrated model estimates the reservoir inflow and flowing wellbore pressure at each lateral of a multilateral well, then predicts the anticipated pressure drop across each ICV for any given flow rate. By knowing pressure and flow distribution in a well system, the flow rate distribution can be balanced by operating ICVs to achieve better flow conditions. This analytical model provides the engineers with a hands-on tool to select proper ICV positions for each lateral or segment and helps optimize the well production. Examples at field conditions are used in the paper to illustrate how the model can be used to improve well performance. Applications such as preventing crossflow in commingled multilateral wells are also presented in the paper.
The performance of a gravel pack sand control system is analyzed considering the potential screen damage associated to the gravel mesh size, which is the key-parameter for designing efficient gravel pack systems. Indeed, the largest mesh size able to reduce solid production while keeping the head loss as minimal as possible, would always appear to be the logical choice. However, screen integrity should also be considered whenever choosing the gravel mesh size, and experimental results presented in this paper show that the larger the mesh size, higher is the chance of localized damage appearing on the screen of the gravel-pack system.
Experimental tests with gravel pack prototypes were run in a large poliaxial frame, using two of the most common gravel sizes: 16/20 and 20/40 mesh. The system was set on artificial cubic rock samples of 11.8 in side, with a centered hole of 2.4 in diameter. The cubical samples were submitted to a triaxial stress field reaching the ratio SMAX/Smin equal to 1.6.
Visible localized damage in the screen's outer surface was observed when testing the larger gravel agent (16/20 mesh), as compared to the smaller 20/40 mesh. The experimental observation was explained by contact stress effect, indicating that larger particle sizes are more prone to damage the screen, while the stresses transferred by smaller particles are more uniform. On the long run, the contact stress effect can result in erosion and, in some cases, screen collapse. A simple, qualitative, analytical model is employed to corroborate the mechanical effects observed in the experimental test.
Whenever designing gravel pack systems for deepwater wells, one should consider long term operation, avoiding complex and expensive workover operations. Thus, a more conservative design criterion is recommended to improve the gravel pack operational life, including the analysis of possible contact stress effects.
Lecampion, Brice (Schlumberger) | Cooksley, Geraint (Altamira Information) | Loizzo, Matteo (Schlumberger Carbon Services) | Arnaud, Alain (Altamira Information) | Robles, Javier Garcia (Schlumberger) | Zhang, Zhun | Sheng, Xiaowei
Time-lapse lapse interferometric synthetic aperture radar (InSAR) images provide accurate surface deformation over a large area and are sensitive to fluid injection/production at industrial scale. The quality and quantities of surface deformation time series open new opportunities for reservoir management. In this paper, we investigate the resolution of pore pressure change from InSAR highlighting some intrinsic features of such type of measurements (i.e. loss of resolution with distance to source). Depending on the relative ratio of the reservoir depth over the source lengthscales (e.g. reservoir extent), we propose two new robust inversion schemes consistently tackling the issue of loss of resolution without additional information: i) multipole moment decomposition for far-field case and ii) decomposition of the pore-pressure field change via Chebyshev series truncated at the order governed by the expected resolution. The example of the Krechba field illustrates our discussion. In particular, we show, using a far-field decomposition that the center of the pressure source remains in the reservoir layer around the KB501 injector and we recover quantitatively the direction of the flow anisotropy. We also discuss the direct inversion of the pore-pressure changes via Chebyshev decomposition. The requirement of a fast but accurate enough geomechanical model is emphasized in order to integrate time-lapse InSAR images with other conventional measurements for history matching purposes. Surface deformation measurement obtained via interferometric synthetic aperture radar (InSAR) is increasingly used in the context of reservoir monitoring (Arnaud, A. et al. (2009)). Time-lapse InSAR can provide surface displacement due to reservoir pressure changes at a millimetric resolution over a large area. Our goal is to review in detail the inversion of such surface displacement data. We believe that InSAR technology is a promising technique for reservoir management, if its advantages and drawbacks are properly understood - especially with respect to what details of the reservoir dynamics can be resolved and how.
In gas condensate reservoirs, deliverability starts to decrease when retrograde condensation occurs. As the bottom-hole pressure drops below the dew-point, gas condensate and water build-up impede flow of gas to the wellbore. In order to stop the reduction in productivity, many publications suggest wettability alteration to gas-wetting as a permanent solution to the problem. Previous simulation work suggests an "optimum wetting state?? to exist where maximum gas condensate well productivity is reached. This work has direct application in gas-condensate reservoirs, especially in identifying the most effective stimulation treatment which can be designed to provide the optimum wetting conditions in the near-wellbore region.
In this work, we aim to show the existence of such an optimum state of wettability that result in maximum gas mobility and in an increase of the relative permeability curves. We present an experimental study on Berea sandstone rocks treated with a fluorinated polymer and investigate the optimum fluorinated polymer concentration that would alter the wettability to intermediate gas-wet. Different experimental techniquesincluding flow tests and spontaneous imbibition are conducted to examine the effect of treatments on wettability. Interaction between rocks and the fluids is studied using a MicroCT scanner.
The studies in this area are important to improve the productivity of gas condensate reservoirs where liquid accumulates, decreasing production of the well. Efficiency in the extraction of natural gas is important for the economic and environmental considerations of the oil and gas industry. Wettability alteration is one of the newest stimulation methods proposed by researchers, and shows great potential for future field applications and further research studies.
Quantifying uncertainty in hydrocarbon production forecasts is critical in the petroleum industry because of the dominant role uncertainty quantification plays in reservoir management decisions. An efficient application of global optimisation methods to history matching and uncertainty quantification of real complex reservoirs has been an extensively an active area of research. The goals of these methods are to navigate the parameter space for multiple good fitting models quickly and identify as many different optima as possible. Obtaining multiple optima can result in an ensemble of history matches that has divergent prediction profiles for more accurate and reliable predictive uncertainty estimates.
The present study extends the application of particle swarm optimisation to handle multi-objective optimisation in reservoir history matching context. Previous research studies in assisted history matching primarily focused on optimising a single objective function in which all the production data coming from the wells are aggregated into a single misfit value. The single misfit value is constructed by summing the weighted squared differences between historical and simulated production data. In the multiobjective optimisation scheme, multiple objectives can be defined representing each or some of the weighted squared difference of
a production type. By constructing multiple objectives that measure the contribution of each objective in the multi-objective optimisation scheme, it can be possible to find a set of solutions which optimally balances the different objectives simultaneously while maintaining solution diversity. The advantage of this construction is that the tradeoffs between the objectives can be explored and explicitly exploited in the course of optimisation to find all possible combination of good fitting model solutions that have similar match quality. In history matching, it is desirable to have various solutions that map to relatively similar low misfit values that can represent all the possible geological scenarios. The new multi-objective particle swarm optimisation uses a crowding distance mechanism jointly with a mutation operator to preserve the diversity of solutions.
In this paper, the multi-objective particle swarm optimisation scheme has been investigated on history matching a well-known synthetic reservoir simulation model and the results were compared with a single objective methodology. Analyses of history matching quality and predictive uncertainty estimation based on the resulted models have been conducted to obtain the uncertainty predictions envelopes for both strategies. The comparative results suggest that, for the reservoir under consideration, the multiobjective particle swarm approach obtains better history matches and has achieved over twofold faster convergence speed than the single objective approach. The benefits of using multi-objective scheme by comparison with the single objective scheme to obtain a diverse set of history matches while reducing the number of simulations required for achieving a similar matching performance have led to more reliable predictions.