OBJECTIVE / SCOPE The Black Sea is a Mesozoic-Cenozoic closed sea system representing one of the last few exploration frontiers in the vicinity of the European market. The overall prospectivity of the basin and associated regional prospective trends have been delineated using the integrated Play-Based Exploration approach. The tectonic evolution, basin formation, sedimentary infilling history, petroleum systems, and sedimentary plays have been investigated to search for new hydrocarbon potential in the basin. METHODS, PROCEDURES, PROCESS The seismic interpretation and mapping were based on 26 sparse 2D seismic lines (ION SPAN), which were acquired and processed in 2011-2012 by ION GTX. The multi-client data from offshore Russia, Crimea, and Ukraine were excluded due to geopolitical sanction. The seismic interpretation which was completed in the depth domain (PSDM depth) was calibrated using three Deep Sea Drilling Project (DSDP) wells namely Sites 379, 380, and 381 ( Fig. 1 ) which penetrated only the shallower section namely the Top Miocene and Top Pliocene. However, the seismic markers where lacking well penetration were primarily interpreted based on seismic stratigraphy. Interpretation of the acoustic basement as well as crustal types were supplemented with gravity and magnetic data from Getech Globe’s database. Three key seismic lines ( Fig. 1 ) were then selected to illustrate the overall basin geomorphology, structural evolution, and to subsequently identify play potential within the basins. The structural analysis was integrated with the seismic sequence stratigraphic analysis to understand the sedimentation history, depositional trends, kinematic evolution, and tectonic history.

In today's fast paced and challenging oil industry, the need of faster evaluation studies for quick generation of field development plan (FDP) is becoming more crucial to remain competitive. Field's geological and structural complexity, uncertainty of production data adds to the challenges. Traditional approach of building dynamic mesh models carrying out numerical simulation to history match, then predict has always remained time consuming in large mature fields. The ‘B’ field in Peninsular Malaysia is a mature clastic with stacked reservoirs having a huge gas cap with moderate aquifer. Significant production over last 30+ years led to uneven movement of the gas cap and also of the edge aquifer leading to possibility of bypassed oil. The updated dynamic model could not match the preferential gas cap movement, thus failed to match the high GOR of downdip wells and also unable to match high watercut of certain updip wells. To identify the areas of bypassed oil thus is a significant challenge with the current dynamic model. New engineering tools of polygon balancing, material balance, normalized EUR bubbles were used with the 3D static model volume and the facies understanding. The uncertainties and risks were also identified and clear measurable methods were proposed to address the uncertainties and reduce the risks. Very detailed decision tree with clear data gathering plan to drill successive optimum wells have been planned during the campaign. This paper details the new engineering tools used to delineate and quantify the bypassed oil in these huge clastic reservoir with preferential gas and water movement, unable to be history matched by the dynamic model. It explains the engineering methods applied to identify and quantify the 10 infill wells proposed for the development campaign. To reduce risks, this paper would also explain the blind testing that was carried out on for this new reservoir engineering analysis tool by deriving the infill potentials of the previous campaign (4 years back) by the same method. The paper details how robust technical development plans were generated having infill well locations and reserve determination. This paper will also demonstrate the classic "Do-Learn-Adapt" strategy through its infill wells prioritization & ranking, subsurface de-risking analysis, data acquisition and mitigations plans.

Shale field operators have vested interest in optimal spacing of infill wells and further fracture optimization, which ideally should have as little interference with the existing wells as possible. Although proper modeling has been employed to show the existence of well interference, few models have forecasted the impact of multiple inter-well fractures on child wells production to optimize further hydraulic fracture designs. This study presented a rigorous workflow for estimating the impacts of spatial variations in fracture conductivity and complexity on fracture geometries of inter-well interference. Furthermore, we applied a non-intrusive embedded discrete fracture model (EDFM) method in conjunction with a commercial black oil reservoir simulator to investigate the impact of well interference through connecting fractures by multi-well history matching, based on a robust understanding of fracture properties, real production data and wellbore image logging. First, according to updated production data from Eagle Ford, the model was constructed to perform four (parent) wells history matching including five inner (child) wells. Later, fracture diagnostic results from well image logging were employed to perform sensitivity analysis on properties of long interwell connecting fractures such as number, conductivity, geometry, and explore their impacts on history matching. Finally, optimal cluster spacing was recommended considering interwell interference. The simulation results show that well interference is present and reduces effectiveness of the fracture hits when the connecting fracture conductivity, primary fracture conductivity, and number of connecting fractures increase. Because of these interwell long fractures, the bottomhole pressure behavior of the parent wells tends to equalize. Furthermore, the EDFM application is strongly supported by complex fracture propagation interpretation from image logs through the child wells in the reservoir. Through this study, three possible scenarios are shown with robust history matching of the model considering more than 20 complex dominant long interwell fracture hits and more than 2000 hydraulic fractures. The model became a valuable stencil to decide the well location and spacing, the completion staging, and to optimize the hydraulic fracture treatment design as well as its sequence so that it can be expanded to other areas of the field. The simulation results were applied to the field successfully to afford significant reductions in offset frac interference by up to 50% and reduce completion costs up to 23% while improving new well capital efficiency.

Data acquisition remains one of the crucial activities to be consistently executed throughout field life for any oilfield development. Significant operating expenditure (OPEX) is allocated each year to understand reservoir performance, thus reduce uncertainties and enable optimizations. This paper aims to highlight the issues faced during simulation model history matching (HM) process of a waterflood reservoir, including understanding of depositional environment and production data integrity. The output is utilized to improve recovery factor (RF) via infill opportunities and water injection optimization. Field A has run a second shot of 3D seismic in 2006 (first in 1995) and processed into a time lapse, 4D seismic. In 2014, a cased hole logging campaign utilizing the high precision temperature, spectral noise logging (HPT-SNL) tool has been completed to check the integrity and flow contribution of 12 wells in Reservoir-X. Within the same period, a pulse pressure testing (PPT) was carried out to verify the communication between wells, in addition to acquiring regular surveillance data which helped to improve reservoir simulation study. The 4D seismic helped to understand the areal waterflood front movement and explained the water cut trend anomaly in an updip well which experienced earlier water breakthrough than near downdip producers. Moreover, it helped to identify a bypass oil zone which can potentially be an infill location. As most of the wells are on dual string completion, the HPT-SNL campaign helped to improve production allocation of multi stacked reservoirs as well as identify problematic wells which required rectification jobs. The PPT assisted in identifying a baffle zone to explain the poor pressure support observed in some producers in the south from the nearby water injectors. All data interpretations were incorporated into final HM model which subsequently identified infill locations and the reservoir management plan (RMP) was successfully revised. An infill program was executed in 2015, which successfully secured additional EUR of ~9 MMstb. Based on the studies and outcome of the infill campaign water injection optimization helped to improve production and added ~2 MMstb reserves, through voidage replacement ratio (VRR) optimization and oil producer (OP) to water injector (WI) conversion. With these efforts, team could successfully project RF of >55%. This case study demonstrates how acquiring focused surveillance data and their effective integration in performance analysis in simulation study helps to reduce uncertainties, unveils infill opportunities, improves production injection optimization and thus helps to improve the recovery factor in brown fields.

A sandstone formation is showing accelerated production decline during the fully compensated waterflood development. The sporadic well tests suggested that liquid rate was following the non-uniform formation pressure decline, despite the full compensation of the offtakes. The paper presents a multiwell downhole pressure gauge deconvolution technique and associated study on the reasons of non-uniform area formation pressure decline and non-uniform injection water front propagation and resulted in recommendations which proved their efficiency after implementation.

The paper intends to share the ideas and methodology on how to improve history matching and manage uncertainties by integrating the deterministic method and stochastic Experimental Design (ED) approach in the most practical way. The integrated method was applied in the re-development study of an offshore clastic oil Field. In the conventional deterministic approach, history matching is conducted by manually tuning the key parameters to achieve pressure and saturation matching iteratively. The main advantage of the deterministic approach is in providing the opportunity to understand the details of the well and reservoir local behaviors during the history matching exercise. The disadvantages are the workflow yields only a single outcome hence poses difficulty in quantifying the effect of multiple uncertainties and is dependent on the of engineer's subjective. Meanwhile, history matching stochastic workflow assisted by ED is a more systematic procedure built to capture the effect of uncertainties on the range of outcomes. However, the parameters used in the stochastic process is typically of global scale, thus the engineer may lose insight into the localized reservoir behaviors. Furthermore, proxies built in ED, although statistically consistent; do not always conform to the reservoir physics as most of the reservoir mechanisms are too complex for reliable modeling by ED-based proxy equations. Candidate Field re-development study aimed to further improve recovery by infill drilling. Analysis of well production data suggested that the remaining oil was entrapped to the crestal region of the field. Full field simulation work was then conducted to target and quantify the infill opportunity. The integrated approach began with a structured deterministic history matching adopting the well-known stratigraphic method. The deterministic history matching involves mostly local modifications of the aquifer strength, fault sealing and well's PI multiplier to achieve satisfactory match on the well and reservoir level. This was then used as the starting base case for the ED workflow. ED History Match led to multiple best matched cases, which were then run in forecasting mode and yielded a range of outcomes. ED History Matching also proved to improve the match quality of the initial deterministic history matched model. Sweet-spotting exercise was performed based on multiple History Matched models and suggested 3 infill potential locations in the major reservoirs, providing three concepts of infill drilling: unpenetrated fault blocks, crestal oil accumulation and sub-optimum drainage area. After considering the risk and confidence level of each potential location, the crestal oil accumulation was selected as the most attractive. Having multiple best match models helped to provide the range of incremental UR that is consistent with the range of uncertainties. The study demonstrated that integration of deterministic and stochastic history matching method has been instrumental in managing uncertainties and identifying redevelopment opportunities of a mature waterflood field.

Prospects below or near shallower producing fields can be economically attractive yet also risky since reservoir presence may be uncertain, reservoir quality can be poor, and high overpressure and temperature can make drilling and logging deeper prospects difficult. Systematic integration of relevant subsurface data from thin section to basin scale allows to seismically identify reservoir presence, and to predict reservoir quality for applicable rock types via burial histories. On an intermediate well log to seismic scale, a predictive rock physics modeling approach links reservoir and seal rock properties to seismic amplitude data to polarize the prospect's geologic ‘probability of success'. Particular challenges in the offshore Brunei study were very fine-grained deposits and non-vertical tectonic stresses associated with compressional settings. Both make porosity predictions that leverage complex burial histories rather than relying on extrapolated depth trends quite challenging - yet the integrated approach remains the best option to identify deep reservoir quality sweetspots that a favorable stress and temperature history may have preserved for certain reservoir rock types in certain locations. The prolific petroleum system offshore Brunei features two major sediment fairways, the Baram and Champion river systems, and a variety of depositional environments, ranging from high NtG topsets inboard over shallow marine slope settings to deepwater turbidites outboard ( Gartrell et al., 2011 ). Across Brunei Darussalam, the systematic ‘Earth-Model’ study, jointly undertaken by BSP and SDB, defined gross depositional environments (GDE maps) and calibrated a 3D basin model. The study leveraged newly reprocessed Broadband seismic data that over large areas had improved imaging of the subsurface. Complementing this regional geologic evaluation with the goal to assess deep reservoir quality, in the here presented study multiple reservoir and bounding mudrock facies were identified and their composition and texture determined from thin sections. Present day porosity and cement volumes were then calibrated and blind tested with burial histories from the basin model. The reservoir quality calibrations will be applied to predict expected present-day prospect reservoir quality. In parallel, sand and shale acoustic properties were calibrated for applicable rock types to allow for quantitative seismic interpretation of reservoir-seal reflectors and to establish the regional ‘amplitude floor'.

Finding an opportunity to expand the recoverable reserves in a brown field is always a challenging task. A robust reservoir characterization and dynamic synthesis are vital to provide a proper understanding of the field. The objectives of this project are to maximize gas recovery through 3D reservoir modeling works, to evaluate un-connected hydrocarbon volumes, production improvement, and prudent reservoir management. Muda Central field (MCF) has been producing for more than 5 years with 40 production wells. Therefore, the production data is an essential input to assure the quality of the model. The geological-facies modelling was constrained by seismic attributes as quantitative soft data after calibrating to well data. The high uncertainty of reservoir presence in the model was assessed by combining sand distribution and porosity variation. Material balance analysis was used to select a base-case static model in order to reduce the iteration process during the history match. History matching was performed with a reasonably good match to calibrate the model. The results of dynamic simulation indicated some potential undrained hydrocarbon areas that are promising for future development. As a result, one well was proposed to appraise and prove the existence of disconnected hydrocarbon volume as recognize in the seismic attributes. The well was drilled a year later to prove the hypothesis. The drilling result demonstrates that the initial hypothesis is proven by pressure data and fluid sampling. The reservoir pressure is still un-depleted and the level of CO 2 content is different compared to the existing producing wells. This finding provides an opportunity for future development in the vicinity of the existing producing platform as well as a different development scheme in the area of the appraisal well. The additional benefit of this work is to assist with prudent reservoir management. A comprehensive model of MCF demonstrates a best practice, collaborative interaction between geophycisist, geologist, and reservoir engineer. This study successfully proved disconnected hydrocarbon volume, which translates into a future development plan to optimize MCF reserves.

This paper presents a fast turnaround Integrated Reservoir Modelling (IRM) workflow for a deep water turbidite field. It is based on a static and dynamic Experiments of Design (DoE or ED) workflow that is used as a toolkit for uncertainty management. The case study shown here emphasizes the application of this "Multi Scenario Approach" methodology for field specific decisions such as short and mid-term reservoir management optimization and infill development opportunities, including impact of key subsurface uncertainties on these decisions. anonumously The objectives of Integrated Reservoir Modelling workflow presented here are: To create fully integrated models or multiple scenarios that provide realistic ranges of forecasts, e.g. geologically sound, to underpin development and operational decisions without anchoring to a single base case; and To shorten modelling life cycle to achieve faster project delivery and allow for uncertainty workflows as proposed in this paper. There are many decisions that are dependent on model forecasts such as identifying infill well target locations and number of wells at the project level, project phasing to extend production plateau, and to identify and mitigate key projects technical risks

The main objective of this paper is to present the assessment and methodology that would improve the tight oil recovery by hydraulic fracturing (HF) wells. The methodology is enabled by a fully integrated workflow orchestrating petro-physical log interpretation, static modelling, and dynamic modelling coupled with rock mechanics for an optimal fracturing design and mitigating the underlying risks. In the past, well placement in tight reservoirs and HF design were performed mostly based on available analogous data of offset wells using rock mechanics parameters such as stress magnitude and regional stress orientation to predict the fractures that would propagate through the reservoir in a certain location and well orientation, the stress/strain regime is one of the key parameters that plays an important role. It is also the key performance indicator for developing the tight oil reservoir with underlying complexities. The process is initiated by the conventional static modelling which involves structural framework construction, distributing the petro-physical characteristics subject to the well logs and other available subsurface data. The second step is to perform a history match of a derived dynamic model by honouring the observed data. This process helps in calibrating the model to be able to represent reservoir dynamic behavior. The results of the history matched model; i.e., reservoir pressure through time is the key input for the Mechanical Earth Model (MEM) in the next step. The MEM process starts with the construction of a 1D MEM using well log advanced scanner and rock mechanics properties from laboratory to represent the strength and elastic properties of the rock where existing wells have been penetrated into the reservoir layers. Hence, a coupled dynamic reservoir simulation with 3D geomechanical model will yield a realistic relationship between the current reservoir depletion state in terms of pressure and the current stress strain regime. This relationship is paramount for optimal location indentification of the fracturing wells and corresponding design together with an estimation of the subsequent recovery. Also, the rock mechanic simulation study would yield a comprehensive result with respect to the reservoir mechanical integrity while conducting the hydraulic fracturing operation to increase the well productivity. This integrated workflow is considered as the key step for tight oil reservoir development, and it can be expanded to unconventional resources for a better reservoir characterisation and reservoir development. The study was performed within close collaboration within the teams with comprehensive know-how sharing and exchange.

The giant field is a geologically complex, faulted anticlinal structure trending east-west, with dips ranging from 0 to 60 degrees. After the current waterflood operations are completed, it is estimated that about 2/3 of oil originally in place will be left behind unrecovered. The combination of light oil gravity and relatively high reservoir pressures makes these reservoirs good candidates for miscible CO 2 EOR. There are separate waterflood developments that have been identified as candidates for CO 2 EOR. Results of the CO 2 pilot provide further encouraging results that show better than expected CO 2 injectivity and vertical sweep than waterflood and good displacement of the remaining oil saturation. The subsurface team successfully used design of experiments to manage uncertainties in history matching and production forecast. Multiple static realizations honoring the key geological uncertainties were built. Based on ranking criteria developed, there were three static realizations chosen for history matching; that resulted in good history matches obtained for five different realizations. The history match model includes all the 500 wells, 70 years of historical production and water injection. All the history matches were within uncertainty ranges and were technically assured for use in CO 2 EOR forecasting. Sector modeling was used to identify and rank different subsurface uncertainties and decisions. Experimental design was used to manage the uncertainties remaining after history match. Hundreds of realizations were simulated that incorporated several integrated development decisions such as injection scheme, development sequence, well spacing, completion strategy and well orientation. Simulation results for all the realizations (with different levels of heterogeneity) indicate that the range of recovery factors varies from 10% (P10) to 24% (P90). The simulated forecasts were also benchmarked against limited analog fields. The production curves are then upscaled to the whole field using a dimensionless curves approach in WellSpring. A methodology to integrate inputs from multiple disciplines (surface, subsurface, wells and CO 2 source) was developed to different integrated filed development options. The complexity, depth, and compartmentalization of the field create challenges that affect all aspects of the CO 2 EOR field development including: scope for CO 2 recovery, flood design options, data gathering needs, integration with existing waterflood, utilization of existing comingled wells, surface facilities and subsurface modeling for realistic production forecasting. Our work focuses on the selection of field development concepts and determining the economic viability whilst incorporating the best practices and lessons learned from the CO 2 EOR industry to ensure top quartile performance.

This paper presents a methodology contributing to describe the filing of petroleum reservoirs based on the quantification of fluid alteration processes. Biodegradation of hydrocarbons in oil reservoirs is one of the important alteration processes of petroleum. Described by Bastin in 1926, it is a widespread mechanism. Hydrocarbon degrading microorganisms have been found until 4 km depths and temperatures ranging up to 80 °C . The alteration of oil leads to an increase of sulphur and metal compounds, and also to the increase of acidity, viscosity and density. The level of biodegradation is classically described by the presence of biomarkers presenting specific resistivity to biodegradation (Peters and Moldowan, 1993). Haeseler et al. proposed in 2010 a quantitative numerical model based on stoichiometric equations, describing, step by step, the evolution of hydrocarbon composition and physical properties in biodegraded oils. This tool was applied successfully to different African Basins (Lower Congo Basin, Niger Delta Basin and Albert Lake Basin) showing excellent correlation between the computed and the analysed composition of oils presenting increasing biodegraded grades. The biodegradability coefficients of the different hydrocarbon classes were shown to follow always the same rules. In the present paper, we applied the dynamic version of this model. In addition to the compositional data, parameters provided by Basin simulators like expulsion history from the source rock, reservoir temperature curves, reservoir volumes… were integrated. Applied to a biodegraded play located offshore Africa, this biodegradation model allowed various parameters describing the filling history of the Oligocene and Miocene reservoirs to be determined: total quantities of hydrocarbons lost by biodegradation, total quantity of methane generated. This allowed to calculate the methane losses over geological times by taking into account presently measured GOR and GOR expected from the numerical simulation, gas loss fluxes: providing a geological description of reservoir sealing efficiency, the kinetic parameters of the biodegradation for each compound class, oil filling path in the reservoirs. The oils from the Miocene reservoirs must have previously been stored (and altered) in the Oligocene reservoirs. A direct arrival in the Miocene reservoirs from the source rock was excluded, the storage time of the oils in Oligocene and Miocene reservoirs. This multidisciplinary work allows to be optimistic about the possible existence of a general law governing the kinetics of the biodegradation and applicable for sedimentary Basins. It also showed that a qualitative and quantitative description of an oil alteration process contributes to a better understanding of fluid paths and the nature of fluids in place. It builds a strong scientific base for the description of fluid differences at reservoir scales that can be applied for various geochemical applications.

This paper describes the development and deployment of a customised, on-line well integrity management system that has resulted in a major improvement in the effective and timely identification, diagnosis and remediation of well integrity issues in RasGas operations. The system, which was built in-house on a web portal, is a business-driven, interactive and collaborative solution that integrates well integrity surveillance data (annuli surveys, integrity tests, corrosion log results, etc.) with maintenance schedules, and provides timely reporting of potential or observed integrity problems and harvesting of historical well data. This enables RasGas engineers and operations personnel to make informed and timely decisions on well integrity to ensure continued safe operation and a high level of well reliability and availability. Key features of the system include effective visualisation of safety-critical elements and operating parameters from the field, effective tracking of integrity testing and preventive maintenance activities, use of "surveillance-by-exception" principle under which the system sends out a notification to all key personnel if any integrity-critical parameter on any well falls outside pre-established limits. The paper will illustrate the effectiveness of the system with actual field examples. Planned enhancements such as incorporating well failure models and individual well risk rating system will also be described. While there are a number of packaged well integrity management tools available in the market, the uniqueness of RasGas system lies in its in-house development which has resulted in seamless integration with the existing data telemetry and processing workflows, flexibility in incorporating customised solutions and ease of scalability to accommodate increasing well count. The paper describes the key factors that contributed to the successful development and deployment of the system, including buy-in from all stakeholders, continuous feedback from field personnel and timely familiarisation and training of the end users.

Within recent years there have been significant research efforts towards building an ensemble of reservoir models to quantify subsurface uncertainty. The data assimilation and model calibration strategy is rapidly moving away from conditioning just a single model as in almost every forecast exercise the predictability of a single model is rather limited. In this paper we will present a frequentist inference basis for the dynamic data integration problem in subsurface modeling. Specifically, we’re after deriving small representative sets of reservoir images and how dynamic data affects them. Our approach starts with screening a large ensemble of subsurface realizations holding between 10 4 –10 6 members (or more) where we’re after representatives that are mutually different in terms of their relevant reservoir flow behavior. We propose a reduced representation of the probability distribution of the high-dimensional vector space of all reservoir images defined by flow-like snapshots. This process allows defining a metric space where it's possible to execute cluster analysis and/or heuristic sampling of the high-dimensional geologic space. The result of this stage is a smaller ensemble of dynamically unconditioned eigen-reservoirs without compromising uncertainty that can be used in any stage of field development planning that involves reservoir dynamics. We have used derivative-based techniques available in our in-house simulator to deterministically history match the eigen-reservoirs and provide a solution to the dynamic data conditioning problem. We provide results of the workflow application in a shallow marine deltaic system where 28 years of production data has been successfully assimilated. Our results show a remarkable improvement in the predictability of reservoir models, which is a vital component in the entire hydrocarbon maturation cycle.

Exploration for oil and gas in the ancient Paleozoic–Proterozoic Taoudenni cratonic basin has been revived in the recent years following the documentation of a viable and efficient petroleum system in the Adrar region of Mauritania. In order to gain better knowledge of the thermal history prevailing in the prospective area (Ta7-Ta8 blocks), extensive fluid inclusion and thermochronology studies have been conducted on outcrop samples as well as cores from recent and older wells in the Paleozoic and Proterozoic sections. The results indicate that the Adrar region was affected by complex and variable burial-thermal regimes. A major cooling-uplift event is documented at ~100–150 Ma, possibly resulting in as much as ~3 km sediment removal. Maximum burial temperature in the Proterozoic formations reached ~140–180°C depending on location. Higher temperatures (>200°C) are recorded which are attributed to short-lived heating events related to diabase emplacement, but no evidence supports a uniform thermal event of regional extension. Cooler burial-thermal regimes may have prevailed in the North-Eastern part of the prospective area. Record of petroleum migration is limited to the Meso-Protrozoic and lowermost Neo-Proterozoic formations, below the Lower Assabet (I14) regional seal. This work provides valuable information for future exploration of the Proterozoic section in this part of the Taoudenni basin.

Abstract The oil and gas industry has been revolutionized within the last decade, with horizontal drilling and hydraulic fracturing enabling the extraction of huge amounts of shale gas in areas previously considered impossible and the recovering of hydrocarbons in harsh environments like the arctic or in previously unimaginable depths like the off-shore exploration in the South China sea and Gulf of Mexico. With the development of 4D seismic, engineers and scientists have been enabled to map the evolution of fluid fronts within the reservoir and determine the displacement caused by the injected fluids. This in turn has led to enhanced production strategies, cost reduction and increased profits. Conventional approaches to incorporate seismic data into the history matching process have been to invert these data for constraints that are subsequently employed in the history matching process. This approach makes the incorporation computationally expensive and requires a lot of manual processing for obtaining the correct interpretation due to the potential artifacts that are generated by the generally ill-conditioned inversion problems. I have presented here a novel approach via including the time-lapse cross-well seismic survey data directly into the history matching process. The generated time-lapse seismic data are obtained from the full wave 3D viscoelastic acoustic wave equation. Furthermore an extensive analysis has been performed showing the robustness of the method and enhanced forecastability of the critical reservoir parameters, reducing uncertainties and exhibiting the benefits of a full wave 3D seismic approach. Finally, the improved performance has been statistically confirmed. The improvements illustrate the significant improvements in forecasting that are obtained via readily available seismic data without the need for inversion. This further optimizes oil production in addition to increasing return-on-investment on oil & gas field development projects, especially in offshore environments.

Abstract A large Middle Eastern oil field, located in Arabian Gulf, is producing a 28° API oil from heterogeneous Upper Mishrif Cenomanian carbonates. The mature field is experiencing high water-cuts arising from a complex combination of different water production mechanisms. Despite the high water production, remaining stakes have been identified and will be targeted for future development. The aim was to build a new reservoir model to be used as an evaluation tool for future field redevelopment. Successful field history matching required the combination of four water production mechanisms at field and local scale: natural depletion of tighter interbedded layers, water-drive, small-scale dual medium effects and large scale conductive natural fractures. The major problem was that from the outset, matches were found with different relative contributions of these mechanisms and possibly with less than four mechanisms modelled. In this challenging context, an innovative history matching workflow has specifically been developed and implemented in order to match the full field behaviour. In outline, the work started with a conventional simulation model which is sufficient to handle the material balance of the system, the natural depletion and the water-drive mechanisms. Complexity was then increased by adding small scale dual-medium effects or explicit large scale conductive features using dual porosity – dual permeability modeling to create two separate models. Finally combination of these two models together gives a full field model which captures all the water production mechanisms. This approach has had two main advantages. It allows (1) a progressive understanding of water production mechanisms and their varying contribution towards water cuts across the field and (2) an optimization of running times of individual simulations as the bulk of the pressure matching work, troubleshooting and broad stroke matching were carried out on computationally inexpensive models. The workflow has also allowed an important parallelization of the matching work using several reservoir engineers working on different models. Finally, a successful history match has been achieved and the final model is currently being used to evaluate future development options. Introduction An oil field, located offshore in Arabian Gulf, has been producing since the late 90s from the complex Upper Mishrif Cenomanian carbonates. The maximum oil column thickness is about 80m from top structure to Free Water Level (FWL) and most of the oil in place lies in the transition zone. Because of reservoir heterogeneity and complexity, the field is still being developed using a phased approach. In addition to the main development phases, infill well drilling has been continuous to maximise production and reduce uncertainties. Since the start of the development, the field has experienced a rapid increase in water cut, passing from 10% to close to 90% in less than 15 years. This water cut evolution results from different reservoir heterogeneities which have impacted more or less across the field: main features evidenced to date result from diagenetic imprints (dissolution, karstification and cementation) as well as structural elements (fracture corridors). The current study was launched to build a new history matched reservoir model, integrating the most recent wells results, with the aim of being one of the tools to be used for the evaluation of future development possibilities over the field. The innovative and pragmatic workflow used to build the model has proved successful for the history matching of this complex field and could provide a useful template for other studies of multi-component carbonate fields.

Abstract This paper discusses about the systematic approach to identify and firm up the infill wells and EOR opportunities as part of the redevelopment strategy in a multilayered mature offshore oilfield which has been on production since the last 46 years. The field is located offshore East Malaysia at a water depth of 186 ft. Production performance of the field indicates the current development strategy and practices will yield a moderate recovery which is currently around 26%. It is in "mid-life crisis", facing problems of increasing water cut, high GOR, with bypassed/undrained oil areas and pressure depletion along with aging facilities. In 2010, the study team embarked on full field redevelopment study to evaluate the infill and EOR opportunities. However, building dynamic model and identifying the remaining hydrocarbon from this area are very challenging due to its highly complex nature; thin oil-rims in over 200 multi-stacked reservoirs with individual thickness of 10 to 30ft, occurring at 2300 to 9800ft depth. The intensed faulting subdivides the field into hundreds of small reservoirs in numerous fault-blocks, with varying degree of fault-block communication and aquifer support. Limited reservoir data, including fluid contacts and fluid types, coupled with ambiguity in production allocation due to commingled production, further complicate dynamic modeling and history matching processes. These uncertainties will affect the remaining hydrocarbon volume and distribution, hence the success of redevelopment project through infill and EOR. A systematic approach to evaluate infill opportunities and EOR performance using dynamic modeling, coupled with LTRO (Locate The Remaining Oil) studies will be discussed. The dynamic model captures the complex fluid movement due to heterogeneity and inter-fault block communications, whereas the LTRO provides an independent analysis on the current fluid contacts and remaining oil locations. Both methods complement each other, hence providing better understanding on the targeted reservoir and maturing the infill and EOR targets. Active surveillance and data gathering activities have also been lined up to reduce subsurface uncertainties. All these prove to be a comprehensive workflow to unlock the remaining oil in this complex field, resulting in several sizeable portfolios with potential to increase the recovery factor by 4 to 9%. Introduction The field is a geologically complex field, with hundreds of multilayered reservoirs consisting of sand-shale sequences, and heavily compartmentalized by antithetic faults (Figure 1). Throughout the production life, the field has undergone primary depletion with a peak production of around 64,000 bopd. Several phases of infill drilling campaigns have been executed to arrest production decline and developed the remaining hydrocarbon, however the average field recovery factor (RF) is only 26%.

Abstract Exploring ancient Paleozoic–Proterozoic cratonic basins is a very challenging undertaking because it is often difficult to achieve a good understanding of complex burial/thermal histories and old petroleum systems. As part of an ongoing exploration campaign, two frontier exploration wells were recently drilled in the northwestern part of the Taoudenni basin in Mauritania, targeting Proterozoic clastic and carbonate petroleum plays located at present-day depths between 2.4 and 3.0 km. Both wells were investigated by use of the so-called FIS (Fluid Inclusion Stratigraphy) technique in order to document the performance of a Proterozoic petroleum system in the Adrar sector of the basin. The results permitted to document the existence of 1) petroleum paleo-accumulation and -migration in the Neo-Proterozoic Lower Assabet sandstones and Meso-Proterozoic Atar dolostones, 2) an efficient seal to oil, above the Lower Assabet sandstones, 3) multiple charges of oil of variable maturity in the eastern well (shallower paleo-burial) subsequently lost by leakage, 4) secondary cracking of a primary oil charge, and possibly gas dismigration, in the western well (deeper paleo-burial). This work demonstrates the existence and the functioning of an oil-prone Proterozoic petroleum system, and provides very valuable guidance for future exploration in this area of the Taoudenni basin. It also opens up potentialities to be investigated for Proterozoic gas/oil shale plays. 1. Objectives and context Frontier onshore exploration is presently being conducted in the northwestern part of the Taoudenni basin, Mauritania, with the objective of investigating very old (450–1500Ma) Paleozoic-Proterozoic plays. This is a very challenging undertaking because this very old cratonic sedimentary basin remains largely under-explored today. Two wells were drilled in the early seventies (1973–1974, Ouasa-1 & Abolag-1) and three in the recent years (2009–2013) in the northwestern part of the basin, but no economical discovery was made so far. The present study focuses on two of the most recent exploration wells. They are located in the Adrar region, east of the city of Atar (Fig. 1), and are referred to as well A (western well) and B (eastern well). The Adrar prospective area is characterized by a Proterozoic-Paleozoic sedimentary succession and a Proterozoic petroleum system (Fig. 1). The Meso-Proterozoic series is composed of the predominantly clastics sediments of the Char Group at the bottom overlain by the thick succession of dolomitic carbonates of the Atar Group. The Neo-Proterozoic series is composed of, from bottom to top, the thick Assabet sandstones, the Jebliat glacial deposits and the thick Teniagouri shales. The Paleozoic rocks are essentially clastics of Cambrian (Nouatil sandstones) to Devonian (Tenemouj sandstones) age.

Abstract Development decisions of oil and gas fields are based with many uncertainties within the supporting data. Uncertainties are larger in the beginning which gets reduced with time as more data is acquired and understanding of the field is improved. However, significant uncertainties persist even in mature fields which are case for redevelopment. Therefore, enormous inherent uncertainties need to be characterized, analyzed and incorporated in the simulation study to the extent possible in order to improve the decision making process. This paper discusses the relevance of reviewing and incorporating the field uncertainties related to geological and/or dynamic properties in estimation of incremental volumes in the redevelopment of a mature oilfield. Reservoir models need to be updated through history matching process to reflect actual measurements from reservoir. In this study a workflow to quantify the uncertainty of a mature oilfield of offshore Malaysia and to estimate the incremental oil potential from infill wells has been designed. During history matching process, dynamic and static parameters of uncertainty, relative permeability curve, local permeability around wells, the aquifers? volume and productivity, and contacts between gas-oil, and oil-water have been considered. An objective function is applied for the history matching which consists of the error between simulated and observed data from wells. An "Evolutionary strategy optimization", proprietary to MEPO software is used to obtain multiple equivalent models with high quality. While running an optimization for history matching, the ranges of uncertainty parameters have been narrowed and adjusted the ranges to be used for quantification of uncertainty of Estimated Ultimate Recovery (EUR). In the prediction stage, both filtered models from actual runs and sampled models from Latin Hypercube have been used. This approach not only allows to evaluate intrinsic uncertainty, but also to keep the variety and risk of prediction. Monte-Carlo simulation technique then makes it possible to acquire the distribution of EUR.