A persistent challenge in reservoir modeling is to assign representative values for vertical permeability in reservoir models. It is a common practice to use kv/kh directly from the core measurements but this is not at the same scale as the model grid. It is also frequent to use one value for entire zones. The approach of using a single value applied to a single zone when the reservoir is heterogeneous is not correct and the same can be said regarding using core plug kv/kh as the grid scale is larger than the core plug therefore resulting in a difference in the statistical support of the two measurements. This paper describes the technique to understand reservoir vertical connectivity by properly defining kv/kh, which later will be used as a matching parameter during the History Match process. Most of the time the data provided by the plugs is not appropriate due to the absence of vertical sampling or to problems of representativeness. Where plug data is available kv/kh ratios are often found to be close to one, a values too high to be realistic when considering the geological heterogeneity at small scale or plug scale. Even when plug measurements show homogenous at small scale (kv/kh ∼1), at grid cell scale the Kv and Kh are expected to be different (<<1). A methodology is proposed in order to give more appropriate ranges of values to the grid cell size, based on the small-scale permeability anisotrophy ratio (kv/kh) into grid cell size. A novel approach was established to get the ranges of kv/kh based on core mini-k measurements and core-plugs data. This innovative workflow also considers a multi-disciplinary approach using Experimental Design methods to better understand and validate the kv/kh ranges. The main learning from this project is the importance of understanding vertical connectivity in a complex reservoir by properly capturing heterogeneity and other major geological features in the integrated 3D dynamic model with the aim to achieve an optimized history match at reservoir level but also more importantly on a well-by-well basis.

Carbonates are infamous for their complex intrinsic heterogeneity, exaggerated due to stratification and layered geology. Characterization and correlation of this heterogeneity with recovery mechanisms becomes critical pertaining to Lower Cretaceous reservoir ‘A’ with over 4 decades of production/injection history. Hence, it is pertinent to systematically reduce the uncertainties associated with reservoir characterization by delineating high permeability streaks, permeability-contrasts, links between geological and petrophysical facies and their impact on field scale production/injection strategies. Emphasis was put on capturing downhole dynamic Kv/Kh profile across sub layers of the reservoir ‘A’, to enable assignment of representative values into reservoir simulation model with associated reservoir zonation. Vertical interference testing (VIT) was designed in a crestal location well with a history of near-by waterflooding, integrating simulator-based outputs with petrophysical and borehole image logs of an offset. Drawdown-buildup cycle was performed across source probe or packer, while simultaneous monitoring of pressure at observation probe. To reduce uncertainty and incorporate statistical sense into the data, multiple cycles of drawdown-buildup were conducted for vertical connectivity evaluation. In total, eleven VIT tests conducted with formation tester tool utilizing dual-straddle-packer and two-probe modules were interpreted implementing a systematic approach considering vertical communication as a function of geological facies and textural aspects from borehole images, geological information on fractures/faults, and surfaces. Interpretation involves identification of flow-units based on available logs, followed by identification of flow regimes (spherical/radial) to history-match data for estimation of horizontal and vertical permeabilities of each layer. Resultant analysis yielded insights on anisotropy by validating vertical communication through stylolite and across dense layers. Integration of VIT analysis results (Kh,Kv,Kv/Kh) with petrophysical logs led to the establishment of water flood advancement mechanism in this observation well at the crestal location of field. This establishes a critical link between integrated geological, textural and facies analysis in context of sedimentology, layering and rock quantified fabric permeability indicators visible on high vertical and horizontal resolution borehole image. Thereby, allowing derivation of scalable answer products and workflows. Subsequently, explaining water flood mechanism and enabling updating of simulation model for enhanced reservoir characterization. Furthermore, this also allows for field development augmentation and injection strategy optimization through linking of dynamic results to reservoir description of two major sub-layers of this giant carbonate field. Integration and analysis of key insights on vertical communication and carbonate anisotropy with major geological/petrophysical features aided in characterizing 3D static and dynamic models. This would allow improved trajectory planning of future wells, leading to improvement in recovery efficiency through guided injection strategy. Additionally, proactive data aggregation and insightful interpretation to help accelerate realization of value from field development strategy was highlighted.

An updated geological and dynamic model for a giant Middle East carbonate reservoir was constructed and history matched with the objective of creating an alternative model which is capable of replicating the reservoir production mechanisms and improving predictability, allowing optimizing the field development plan and water injection strategy. Giant Middle East carbonate fields often have long production history and exhibit high reservoir heterogeneity. It is always challenging to get a robust history matched model aligned with geological concepts and dynamic behavior understanding. The objective of this paper is to present an improved and integrated reservoir characterization, modeling and history matching procedure for a giant Lower Cretaceous carbonate reservoir in the Middle East. The applied workflow integrates all available geological data (stratigraphy, depositional facies, and diagenesis), petrophysical data (RCA and minipermeameter data, Petrophysical Group definition, cut-off definition) and the extensive database of dynamic data (long production history, well test, RST, open-hole log saturation over more than 40 years of development drilling, and MICP). The process was initiated with the reservoir review by means of a fully integrated study that allowed having better understanding of the reservoir behavior and production mechanisms. The key heterogeneities (high permeability and intra-dense layers) which control the flow behavior were identified during this process. Geological trend maps were generated to control the distribution of high permeability and intra-dense in the model. Well test data, open-hole logs from development wells and time-lapse saturation logs from observation wells were used to calibrate the trend and permeability log data. A phenomenological model was constructed to test the main factors impacting the production mechanism as identified during the reservoir review. Multiple iterations were performed between the static and dynamic models in a way that allowed a quick and efficient work that is consistent with all disciplines assumptions. Such continuous loop between the dynamic and geological models, with focus on the geological heterogeneities driving the dynamic reservoir behavior, has led to a more robust model capable of replicate the production mechanisms, which represents a major improvement compared to previous model in term of predictability.

Reservoir model history matching is the solving process of a complex inverse equation mainly relating reservoir and well properties to observed data using a time and space discretized numerical model. A challenging task for engineers but a prerequisite to a vital tool to field development and business planning. This paper presents the calibration of a giant Middle East carbonate reservoir from scratch following a major field review. The objective of this integrated history match was to provide a reliable and sustainable representation of the reservoir in order to: Predict performance, necessary strategies and expenditures for field development Reproduce the fluid distribution and the flow mechanism Represent the areas of the reservoir where there are no data Discover then solve or anticipate any operational issue It is a tedious work to calibrate coherently the static and dynamic models of a Giant field with complex geological heterogeneities, more than a thousand wells and forty-four years of history where multiple scenarios can coexist. This paper will present the workflow used to achieve a reliable and sustainable representation while narrowing down the number of solutions by using: Theoretical and analytical calculations on paper to assess the foundation and physics behind the reservoir behavior Phenomenological models to understand the main drivers and reproduce the flow mechanism with a more flexible tool Regional geology and migration history to estimate untested parameters away from the oil pool especially inside the aquifer An iterative and innovative Static-Dynamic integrated process to generate a reservoir characterization honoring geology and performance at the same time The applied workflow revealed for the first time the magnitude of the natural energy of the reservoir that contributes significantly (15-20%) to the energy loss. A revelation that changed the reservoir development strategy going forward. It inspired innovative methods to capture horizontal and vertical permeability needed to reproduce field performance on surface and flow dynamics inside the reservoir. This comprehensive and integrated workflow generated a reliable and sustainable tool and put in place different technics to achieve an updated history match relatively quickly.

Middle East brown fields are penetrated by, more or less, around 1000 wells with long-production history. Attempts to incorporate all these wells create huge challenge caused by uncertainty related to well data discrepancy. The discrepancy in acquisition methods, tools, vintages are few factors to name that are root causes resulting in different depth values. Therefore, varying depth makes difficult to build structure of 3D reservoir model without non-geological anomalies such as distorted, collapsed, non-orthogonal cells. Methodology is to introduce uncertainty to all data feeding the structure modelling process. Following data is used with their ranges of uncertainties: interval velocity, seismic time maps, thickness maps, geological markers and well surveys. These ranges have to be identified quantitatively as they will give us flexibility to integrate data in the model within justifiable windows. Initially, the maps are allowed to change and try to integrate all data without well survey modifications. If, even after number of iterations, data is still not consistent resulting non-geological anomalies, then it is good to try allowing survey to change, but cautiously. Following application of this workflow, the data started to come in agreement and resulted in smooth, geologically reasonable subsurface structures. Horizontal wells targeting multiple thin carbonates are the most challenging to place them correctly. These wells require a lot of iterations or manual intervention to incorporate in the model, sometimes by adding number of pseudo-wells. Figure 1 shows even those examples can result in geological markers, of both vertical and deviated sections, match structure surfaces where horizontal trajectory at right penetrated layers. Worth to mention that the integration of almost ~1000 wells required zero pseudo-wells that helps to avoid introducing unrealistic noise to the data. Successful implementation of this project made this giant field one of the first brownfields that incorporated all data in consistent manner without using pseudo-wells. This structure model will maximize the value from ADNOC's existing data resources to reduce uncertainties during subsequent property and dynamic modelling stages plus while drilling future wells. Average estimates show that proper integration of all data can bring minimum $18 million in value.