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.
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.
Wei, Chenji (Research Institute of Petroleum Exploration and Development, CNPC) | Zheng, Jie (Research Institute of Petroleum Exploration and Development, CNPC) | Ouyang, Xiaohu (China Petroleum Pipeline Engineering Co., Ltd, CNPC) | Ding, Yutao (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Ding, Mingming (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Lin, Shiyao (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Song, Hongqing (University of Science and Technology Beijing)
Understanding the heterogeneity is critical for a successful water injection in a carbonate reservoir. Thief zone is one of the most obvious forms of heterogeneity, which indicates the thin layer with higher permeability compared to the average reservoir permeability. The existence of thief zone results in earlier water breakthrough and faster water cut increase, which then lead to lower sweep efficiency and smaller recovery factor. Therefore, determining the distribution of thief zone and its impact towards production, and proposing a corresponding development plan are very important.
In this paper, a novel method is established to determine the thief zone distribution based on dynamic surveillance data. A new index is proposed as the relative contribution index to characterize the relative contribution of a certain layer, which is fundamental for thief zone determination. In addition, effect on water flooding development of thief zone's location is studied by experimental and theoretical analysis. The changes of water cut and production rate are analyzed under different conditions such as location of the thief zone, injection rate, and variogram. Finally, optimized development strategy is proposed to deal with the existence of thief zone.
Distribution of thief zone is characterized based on the proposed method, which indicates that thief zone development has intimate relationship with depositional facies and diagenesis. Experimental and theoretical analysis results show that the present model considering stratified water-flood is consistent with the experimental results. The water displacement effect is the best when the thief zone is located in the upper reservoir. This paper also points out the optimal adjustment period for water shutoff and profile control of the reservoir with thief zones. In addition, the greater the injection rate, the faster the water cut increase. Furthermore, the smaller the variogram, the slower the water cut increase, and the later the water breakthrough time.
This study provides a method to characterize thief zone, which can be used as a reference for similar oilfield development. In addition, it provides a quick and reasonable guide in the later adjustment of water flooding development of carbonate reservoirs with thief zones.
The fourth industrial revolution is taking the oil and gas business by storm. Many companies have increased resources for big-data analytics and machine learning. Though no one sees physical oilfield services as in decline, development in these areas may take a back seat to artificial intelligence. This paper covers the staged field-development methodology, including analysis and evaluation of various development concepts, that enabled the company to optimize both completion design and artificial-lift selection, reducing downtime and lowering operating costs by nearly 50%. This paper describes interpretation results of a 4D seismic-monitoring program in a challenging Middle East carbonate reservoir.
Ghawar / Al-Ghawār /الغوار is an oil field located in Al-Ahsa Governorate, Eastern Province, Saudi Arabia. It measures 280 by 30 km (174 by 19 mi), it is by far the largest conventional oil field in the world. It is entirely owned and operated by Saudi Aramco, the state run Saudi oil company. Blue wells are waterflood injectors, red are production wells. In April 2010, Saad al-Treiki, Vice-President for Operations at Aramco, stated, in a news conference reported in Saudi media, that over 65 billion barrels (10.3 km3) have been produced from the field since 1951.
Kirkuk is a supergiant oil reservoir located in Iraq. From 1961 to 1971, 3.2 billion bbl of oil were produced under pressure maintenance by waterdrive using river water. The 1971 production rate was approximately 1.1 million barrels of oil per day (BOPD). Since then, the field has continued to produce large volumes of oil by voidage-replacement water injection; however, few production details for recent years appear in the technical literature. The primary pay interval for the Kirkuk field is the 1,200-ft-thick Main Limestone.
Lei, Zhengdong (Research Institute of Petroleum Exploration and Development, PetroChina) | Xie, Qichao (Exploration and Development Research Institute of ChangQing Oilfield Company) | Tao, Zhen (Research Institute of Petroleum Exploration and Development, PetroChina) | He, YouAn (Exploration and Development Research Institute of ChangQing Oilfield Company) | Zhu, Zhouyuan (China university of Petroleum) | Peng, Yan (China university of Petroleum) | Liu, Canhua (China university of Petroleum)
Waterflooding of fractured low permeability reservoirs are often associated with poor sweep and high water cut due to existence of natural fractures, hydraulic fractures, and artificially induced fractures. Therefore, reservoir simulation with coupled geomechanics and dynamic fractures is required for this application. In this work, we present the use of streamline-derived flux information to improve overall waterflooding performance in such complex simulation problems.
This work shows the waterflooding optimization workflow of a fractured low-permeability reservoir in ChangQing Oilfield, China. First, the finite difference simulator considering stress field and geomechanical properties is used to simulate the growth of dynamic fractures. Then, the newly formed fracture properties are included into the dual porosity/permeability reservoir simulation model. Afterwards, streamlines can be traced based on the velocity field of this model, which represent a snapshot of the inter-well fluxes. Finally, with the goal of minimizing field water production, we implement linear programming algorithms to optimize the waterflooding operation by considering the inter-well connectivity and well allocation factors.
Through reservoir simulation coupled with geomechanics, we have found that induced fracture growth rate is relatively limited at reasonable injection rate, which is also validated by field empirical observations. This can avoid fracture propagation and reduce the risk of rapid water breakthrough. We deploy our streamline tracing and linear programming based optimization program to work together with this simulation model. A controlled and cautious increase in injection rate has resulted in a positive production response in 28 producers in the pilot area. Reallocation of water to high-efficiency injectors improves sweep efficiency in the reservoir. Finally, the optimized scenario has resulted in more than 15% incremental swept volume as compared to the basic development case.
This work provides a comprehensive case study for better understanding the impact fracture growth on waterflooding performance in fractured low-permeability reservoirs. It further establishes the workflow of using streamline-based flux information for oil production optimizations in these complex simulation problems.
As an enhanced oil recovery method (EOR), chemical flooding has been implemented intensively for some years. Low Salinity WaterFlooding (LSWF) is a method that has become increasingly attractive. The prediction of reservoir behaviour can be made through numerical simulations and greatly helps with field management decisions. Simulations can be costly to run however and also incur numerical errors. Historically, analytical solutions were developed for the flow equations for waterflooding conditions, particularly for non-communicating strata. These have not yet been extended to chemical flooding which we do here, particularly for LSWF. Dispersion effects within layers also affect these solutions and we include these in this work.
Using fractional flow theory, we derive a mathematical solution to the flow equations for a set of layers to predict fluid flow and solute transport. Analytical solutions tell us the location of the lead (formation) waterfront in each layer. Previously, we developed a correction to this to include the effects of numerical and physical dispersion, based on one dimensional models. We used a similar correction to predict the location of the second waterfront in each layer which is induced by the chemical's effect on mobility. In this work we show that in multiple non-communicating layers, material balance can be used to deduce the inter-layer relationships of the various fronts that form. This is based on similar analysis developed for waterflooding although the calculations are more complex because of the development of multiple fronts.
The result is a predictive tool that we compare to numerical simulations and the precision is very good. Layers with contrasting petrophysical properties and wettability are considered. We also investigate the relationship between the fractional flow, effective salinity range, salinity dispersion and salinity retardation.
This work allows us to predict fluids and solute behaviour in reservoirs with non-communicating strata without running a simulator. The recovery factor and vertical sweeping efficiency are also very predictable. This helps us to upscale LSWF by deriving pseudo relative permeability based on our extension of fractional flow and solute transport into such 2D systems.