A giant brownfield re-development project with long horizontal wells was initiated to arrest production decline mainly caused by a lack of pressure support and free gas influx from the large gas cap.
Key value drivers for the project are developing an understanding of the layers with regards to gas breakthrough, and achieving capital efficiency through low-cost well delivery, better planning and technology applications.
Firstly, the field has been segmented based on the analysis of multiple factors influencing the free gas production. It considers geological aspects such as the study of depositional environment and diagenesis, structural elements such as high permeability streaks and fractures, dynamic behaviors such as the water injection efficiency, gas cap expansion or coning.
Secondly, numerical simulations were then run in order to rank the sectors based on the expected model performance, compare them with real data categorization, and test the effect of the new proposed development schemes such as water injection at gas-oil contact and long horizontal wells equipped with downhole control valves.
It was found that each sector has a specific production mechanism and appropriate developments were recommended and then tested in the simulation. For instance, high permeability streaks play a significant role on the development of some sectors instigating a big difference of maturity between sub-layers, early water or gas breakthrough. Also, the inefficiency of water injection is one of the biggest issues of the field. Most of the water injectors are located too far from the oil producers, and have a low injectivity due to the often degraded facies in the aquifer because of diagenesis. This leads to a lack of pressure support that is counterbalanced by the gas injection, ending up with a lot of high GOR wells and a bad sweep from the top of the structure as the gas tends to by-pass the oil.
Simulation work showed that several remaining zones are safe for immediate development and should be prioritized for development in the near future. On the other hand, some of the mature layers prone to gas and water breakthrough need a boost for development, such as water injection at gas-oil-contact, artificial lift, low pressure system, GOR relaxation. Tight and undeveloped reservoirs are improved by implementing long horizontal drains.
This paper discusses the re-construction of the long-term development plan for an offshore giantfield located in Abu Dhabi with the aim to mitigate the rising challenges in the maturing field. The primary objective is to understand the reservoir behavior in terms of fluid movement incorporating the learning from the vast history while correlating with the geological features.
The field has been divided into segments based on multiple factors considering the static properties such as facies distribution, diagenesis, faults, and fractures while incorporating the dynamic behaviors including pressure trends and fluid movements.
On further analysis, various trends have been identified relating these static and dynamic behaviors. The production mechanism for each of the reservoirs and the subsequent sub reservoirs were analyzed with the help of Chan plots, Hall plots and Lorentz plots which distinctly revealed trends that further helped to classify the wells into different production categories.
Using the above methodology the field has been categorized in segments and color coded to indicate areas of different ranking. The green zone indicates area of best interest which currently has strong pressure support and wells can be planned immediately. The wells in this area are expected to produce with a low risk of water and gas. The yellow zone indicates areas of caution where special wells including smart wells maybe required to sustain production. This area showed relatively lower pressure support owing the location of the water injectors and the degraded facies quality between the injectors and the producers. The red zone highlights areas which are relatively mature compared to the neighboring zones and will require new development philosophy to improve the recovery. The findings from this study were used as the basis for a reservoir simulation study using a history matched model, to plan future activities and improve the field recovery.
This study involved an in-depth analysis incorporating the latest findings with respect to the static and dynamic properties of the reservoir. This has helped to classify the reservoir based on the development needs and will play a critical role in designing the future strategies in less time.
A reservoir simulation study of different fishbone well designs performance compared to a base development well design of extra-long maximum reservoir contact (MRC) single lateral wells is presented. The objective is to compare different well design concepts in a waterflood recovery scheme to achieve production target rate and maximize resource value for economic development of an undeveloped tight carbonate reservoir. The studied reservoir is located in a giant offshore oil field in the Middle East and was used as a representation of the different tight reservoirs within the field. It is characterized by poor quality rocks with a permeability trending from 2 – 0.5 md in a SE – NW direction.
The study compromises an assessment of the achievable initial maximum oil rate, volumetric reservoir sweep and expected ultimate oil recovery factor for different well design concepts for a base short well spacing utilized for effective pressure support. In addition to that, the impact of fishbone well design on well count reduction potential utilizing twice the base short well spacing compared to single lateral wells development design utilizing the base short well spacing was evaluated.
A sector model with equal producer to injector ratio was used with refined gridding to wells and bulk area gridded with a cell size of 10 m by 10 m in a representative area of the reservoir. The modeled wells incorporated with vertical flow performance tables with gas lift capabilities. The analysis also incorporated generating streamlines for analyzing fishbone well designs areal reservoir sweep and an examination of remaining movable oil areal distribution. An assessment matrix was formulated for comparing extra-long MRC single laterals base development design versus different fishbone well designs. The assessment matrix incorporated in addition to reservoir related flow performance indicators: drilling complexity and well cost, well life cycle activities, etc. for a comprehensive assessment.
The main findings show that fishbone well designs have complicated areal sweep performance, especially with sealed motherbore, that result in a lower oil recovery factor with higher hydrocarbon pore volume injected and water oil ratio compared to extra-long MRC single laterals. Also, fishbone well designs have serious limitations during well life cycle activities compared to extra-long MRC single lateral design in terms of stimulation, well accessibility and well intervention options making the extra-long MRC single laterals the preferred field development concept within tight reservoirs especially with the base short well spacing. Finally, the analysis has shown that Fishbone well designs can’t reduce the well count since base short well spacing is still needed for effective pressure support by water injection in addition to maximizing the oil recovery factor within the field life time and building and sustaining the target plateau.
Waterflooding is the main technic to recover hydrocarbons in reservoirs. For a given set of wells (injectors and producers), the choice of injection/production parameters such as pressures, flow rates, and locations of these boundary conditions have a significant impact on the operating life of the wells. As a large number of combinations of these parameters are possible, one of the critical decision to make is to identify an optimal set of these parameters. Using the reservoir simulator directly to evaluate the impact of these sets being unrealistic considering the required number of simulations, a common approach consists of using response surfaces to approximate the reservoir simulator outputs. Several techniques involving proxies model (e.g., kriging, polynomial, and artificial neural network) have been suggested to replace the reservoir simulations. This paper focalizes on the application of artificial neural networks (ANN) as it is commonly admitted that the ANNs are the most efficient one due to their universal approximation capacity, i.e., capacity to reproduce any continuous function. This paper presents a complete workflow to optimize well parameters under waterflooding using an artificial neural network as a proxy model. The proposed methodology allows evaluating different production configurations that maximize the NPV according to a given risk. The optimized solutions can be analyzed with the efficient frontier plot and the Sharpe ratios. An application of the workflow to the Brugge field is presented in order to optimize the waterflooding strategy.
The high CO2 content of Brazil’s pre-salt fields, which may reach values from 20% to 44% molar, presents both a challenge as well as an opportunity. CO2 stripped from the produced gas cannot be released into the atmosphere due to environmental restrictions. Therefore, the whole amount of CO2 produced should be continuously reinjected into the reservoir. This work investigates the effect of CO2 content on the low salinity water alternating CO2 injection technique (CO2LSWAG) using a commercial compositional reservoir simulator. In these field-scale simulations, CO2 is stripped from the produced gas and reinjected into the reservoir. Primary oil recovery methods such as CO2 flooding and LSW flooding are also simulated. Chemical reactions between CO2 and the minerals present in the reservoir are modeled. Wettability change is assumed to be the main mechanism for improved oil recovery due to low salinity water injection. Compositional simulations of CO2 injection usually assume a constant injected gas rate. In this case, CO2 is supposed to come from an external source. In many petroleum reservoirs this assumption is true. Three factors are assessed in the present work. The first one is the natural reservoir pressure, which is the main driving force in primary production. The second factor is the amount of CO2 available for injection. The third one is the wettability change promoted by the reaction involving CO2. It is shown that in primary production, higher CO2 content leads to quicker depletion of the natural energy of the reservoir, leading to lower oil recovery. Nevertheless, higher CO2 content also means that more gas is available for reinjection, potentially leading to increased oil production. Finally, as CO2 reacts with minerals it promotes a change in wettability from an oil-wet to a water-wet state. It is shown that the CO2 content is an important variable to be assessed in a high CO2 content reservoir. Optimal injection practices must take these three aspects into consideration.
The objective of this work is the prediction of water salinity evolution trend for Mexico Area-1 development that foresees the injection of a mixture of seawater and produced water from the six different reservoirs connected to the same FPSO.
Prediction of salinity trend evolution is crucial for forecasting possible biogenic hydrogen sulphide (H2S) formation and foreseeing the relating impacts over completion and facility material selection and on health, safety and environment (HSE) management.
Traditional numerical simulations through stand-alone models do not consider the effects of the reciprocal interaction among the fields on production profiles and are not able to simulate salinity evolution of produced and injected water mixture, variable over time. To overcome this limit, a new tool was developed. It consists in a python script that, introduced into the Area-1 Integrated Asset Model, allowed to generate forecasts of the water salinity along the project lifetime. These simulations were essential for souring risk assessment, providing the following results: water salinity trend evolution at each injector well; water salinity trend evolution at each producer well; injection water breakthrough timing at the producer wells.
water salinity trend evolution at each injector well;
water salinity trend evolution at each producer well;
injection water breakthrough timing at the producer wells.
Moreover, it gave the opportunity to assess the injection strategy efficiency and to quantify the impact of changing salinity on water viscosity and on the field recovery.
In conclusion, the innovative methodology applied in the Area-1 IAM (Integrated Asset Model) permits to predict the salinity of injected water and to foresee salinity evolution of produced water generating several valuable information, providing a flexible tool that allows to investigate simultaneously several uncertainties related to the project and to evaluate promptly solutions and mitigation.
Moreover, when the reservoirs will be on production, the numerical models integrated with the developed script will reproduce the historical salinity data allowing to identify preferential flow path established by fluids virtually acting as a reservoir tracer technology.
Effective management of Voidage Replacement Ratio (VRR) throughout the producing life of an oil reservoir is essential for achieving optimal oil recovery. VRR is quantitatively defined as injection/production fluid volume ratio at reservoir conditions. The primary goal in managing voidage replacement is to replenish the energy in a reservoir to a degree that the producing wells yield hydrocarbons at economical rates. The determination of VRR, however, becomes more complicated when reservoirs are significantly affected by fluid influxes. This paper presents a method developed to optimize VRR calculations using streamlines, traced from finite-difference reservoir simulation model outputs.
Good reservoir management practice necessitates that conventional VRR should be maintained at or above unity. Maintaining appropriate injection performance is therefore an essential requirement for achieving optimal oil recovery in secondary recovery processes. This can be achieved through effective VRR surveillance, water breakthrough monitoring, and reservoir pressure maintenance.
This paper presents a new technique and associated workflow for rigorous VRR determination that resolves a number of shortcomings inherent in conventional VRR analysis. This rigorous VRRR determination methodology was applied to an existing field with considerable operating history including multiple displacement and recovery processes: primary depletion, aquifer influx, gas re-injection, gravity water injection, and power water injection. This new methodology utilizes finite difference reservoir simulation models to generate streamlines from the pressure field and fluxes. Streamlines represent flow paths between injectors and producers. The streamline trajectories with associated time-of-flight values thus obtained take into account geologic complexity, external fluxes, well locations, phase behavior, and reservoir flow behavior. Rigorous VRR estimates are obtained by accounting for the influxes and well allocation factors (WAF), which represent a measure of connectivity between specific injector/producer pairs with associated fluxes. The fluxes and WAF values are calculated automatically from the history-matched reservoir simulation model during streamline tracing for associated time steps.
Traditionally, the well VRR values are calculated via the formulation of well inflow performance relationship (IPR), which may result in suboptimal estimations by not accounting for external sources of energy, such as influx from neighboring zones. The presented approach allows for improved optimisation of waterflood injection efficiency, where the off-set oil production can be derived directly from reservoir material balance (MB) calculations and streamline-generated well allocation factors. In order to facilitate VRR calculations with dynamic simulation regions, we propose a workflow for streamline (SLN) based VRR calculations using the time-dependent flow-based SLN-conditioned drainage volumes, automatically extracted from the simulation grid and iteratively incorporated into simulation model constraints as a function of simulation run time-steps.
Reservoir A is being developed in early and interim phases in order to gather static & dynamic data to minimize the risk associated to subsurface uncertainties. In early and interim phases, only production is taking places. During full field, water injection scheme will be implemented using mainly 5-spot pattern. It is very crucial to measure the subsurface uncertainties and their impact on the reservoir development. For this purpose, the uncertainty parameters are identified and their ranges are selected based on the current well performances during probabilistic History matching (PHM) phase. In full field runs, the uncertain subsurface parameters are quantified to prioritize the future reservoir monitoring and data gathering plans. Note that wells are equipped with the permanent downhole pressure gauges.
Reservoir A is one of the major reservoirs of a green-field located offshore Abu Dhabi and is being developed with a 5-spot water injection pattern. The producers and water injectors are horizontal wells which are drilled across different flow unit within the reservoir. The reservoir properties are variable across all the flow units, which may results in a non-uniform water front. Being a green field, there are more uncertainties as compared to the brown field. More than three years production & pressure data is available which is used in this uncertainty study. This production data is mainly used to achieve the probabilistic History match on well-wise basis. In this uncertainty study, previous HM parameters are removed. However, based on previous history matching learnings, the subsurface uncertain parameters ranges are selected for this probabilistic History match phase. The criteria for filtering the valid runs during this phase are set to be ±150 Psi compared to the actual downhole pressure readings. In case of decreasing this filtering range to 75 Psi, results in reduction in the reserve range in P90 to P10. Based on ±150 Psi principle, the subsurface parameter ranges are furthered reformed for full field uncertainty study/run. The industry standard workflow is followed to quantify the subsurface parameters during this phase. In this study, we used the Permeability modifiers based on RRT, Faults transmisibilities, Relative Perm curves (based on SCAL data), Kv/Kh ratio (from PTA), etc. as uncertain parameters. The impact of each parameter is measured and quantified with respect to plateau and total reserves.
Production optimization is the method for seeking the best possible well control and schedule plans in order to enhance reservoir performance under a given state and economic constraints. Determining the optimal injection and production control strategies through adjoint gradient-based optimization is a well-known practice in today’s modern reservoir management. However, apt handling of nonlinear control inputs, state and output constraints can be quite tedious with effects on the computational efficiency of the optimization algorithms used in practical production optimal control problems. In this paper, we develop an adjoint based interior-point inexact trust filter sequential quadratic programming (IITRF-SQP) method for solving constrained production optimization problems. Inexact trust-region is an extension of a filter trust region approach, which is used when the control input constraints Jacobians are of high dimension and are expensive to compute. The output constraints are handled using an interior-point method called- modified barrier-augmented Lagrangian, in which inequality constraints are treated by a modified barrier term and equality constraints with augmented Lagrangian terms. The algorithm we present uses the approximate information of Jacobians achieved through composite-step computation, which eliminates the cost of direct calculation of Jacobians and Hessians (gradients). The gradient information that provides criticality measure of the objective function is calculated using the adjoint method. Two numerical experiments on optimal water-flooding are presented. Performance comparisons of the proposed IITRF-SQP method with Lagrangian barrier method and sequential linear quadratic programming (SLQP) for solving production optimization problem are carried out. Results indicate that the gradient-based adjoint coupled with IITRF-SQP was able to improve net present value (NPV) through optimal production profiles with better computational efficacy via reduced convergence time and number of gradient and objective function evaluations.
Mendoza, Maria (Petroamazonas EP) | Cevallos, Gonzalo (Petroamazonas EP) | Molina, Edison (Petroamazonas EP) | Piñeiros, Silvia (Petroamazonas EP) | Torres, Water (Petroamazonas EP) | Garrido, Johnny (Petroamazonas EP) | Gutierrez, Ruben (Schlumberger) | Fonseca, Claudio (Schlumberger) | Cortez, Oscar (Schlumberger) | Fernandez, Edgar (Schlumberger) | Paladines, Agustin (Schlumberger)
An Ecuadorian lease ("Bloque 61") composed of 14 oil fields represents the most productive asset in the country. It contains 5.3 billion barrels of original oil in place (OOIP) distributed in four complex producing reservoirs. After 44 years of production and with a decline rate of 31% per year, maintaining the production from these fields represents an important challenge from the subsurface and execution viewpoints. In December 2015, an integrated service contract was signed with the national oil company (NOC) with a fixed investment for the development of the entire lease.
The challenge of the project was to maximize the value of a depleted asset through the framework of the c ontract. This mature asset has many opportunities to boost production and reserves by implementing an aggressive fit-for purpose development. The opportunities screened and implemented in only 12 months consisted of reaching new oil in appraisal and exploration areas and redevelopment of mature zones with horizontal and infill drilling with mainly reentry wells. Most valuable of all was the implementation of six waterflooding projects. All of these were executed in the Amazon rainforest where there is a pressing need to reduce environmental and social impact.
This exploitation philosophy has successfully changed the asset's production decline, ramping production up from 60,000 BOPD to 80,000 BOPD. This integrated field development plan has amalgamated several technologies with a specific objective of optimizing the value of the asset. The long term was assessed through the drilling of exploration and appraisal opportunities where prospective resources were recategorized to reserves. The medium term was tackled by drilling horizontal wells and re-entries to optimize sweep efficiency and implementing water injection in the main structures. The short term was directed by executing workovers in areas where the water injection was in place. The asset value was recovered and increased as shown by a reserve's replacement ratio of 1.13.
This approach will serve as a framework for the future integrated development of these types of mature assets. The technologies implemented have helped accelerating and optimizing the conceptualization and execution of the project; a few of these include high-resolution reservoir simulation, dumpflooding, closed-loop water source system, and dual-string completions. The integration of strong domain expertise, coupled with advanced technologies and workflows, has led to outstanding results.