This paper presents a method to condition the permeability modeling of a thin, heterogeneous high-K dolomitized unit. The interval is an important drilling target for field development, so precise permeability modeling is required to optimize well placement and completion designs in order to maximize oil recovery and minimize early water breakthrough. Detailed core observations from 85 wells classify the unit into two groups: Group A, composed mainly of dolostone and Group B, comprised exclusively of calcareous dolostone. Regression analyses of plug porosity-permeability values are characterized by one regression line for each group by which dolostone represents a higher permeability trend relative to calcareous dolostone. Core-plug scaling is used to scale-up the porosity-permeability relationships from core plug- to modelscale (100 m by 100 m cells). The two regression lines accurately capture the permeability contrast within the dolomitized unit. To extend the method into a full-field model, it is necessary to calibrate the well logs to the core data. Comparison of cores with various log responses indicates the porosity log is the most useful tool to achieve this. Group A, characterized by higher dolomite content, is distinguished by a distinct decrease in the porosity due to progressive dolomitization. Porosity logs from 499 wells are interpreted and permeability values are assigned using the regression lines based on the detailed distribution map of both groups. The modeling approach using hundreds of well logs calibrated to cores yields a more detailed picture of the spatial permeability variations of the dolomitized unit. Dynamic data from ongoing history matching is also used to implicitly adjust the first-pass static model.
This paper is a comprehensive analytic driven study on the use and sizing of membrane filters to improve the injected water quality for maintaining injectivity in tight carbonate reservoirs. Out of the different mechanisms of formation damage, the pore plugging with the migration of particles within the injectant fluids by bridging at the pore throat junctions and/or by pore filling can lead to the buildup of an internal filter cake away from the wellbore that limits the well’s injectivity and can affect the vertical and lateral sweep. This type of formation damage is very difficult to treat with any kind of stimulation and the impact will be manifested especially in tight formations with interbedded stylolites layers with a total range of permeabilities from 2 to less than 1 milli-Darcy and a median pore throat size ranging from 2.5 to 0.3 micron meters. The study comprises several parts starting with a geological analysis that was conducted to identify areas and layers most prone to formation pore plugging by analyzing thin-sections and MICP data. Second, in the lack of core flood tests, a reservoir and well study analyzed existing water injectors situated in similar or slightly higher quality rock areas through the analysis of injectivity index behavior to estimate the impact of damage and the expected injector’s half-life. As a result, through the application of an analytical mathematical model for defining deep bed filtration parameter, a correlation was established based on average injected particle size and reservoir rock quality to aid in selecting the proper water injection filter size. In order to confirm that, a dedicated injectivity test in a horizontal well utilizing membrane filters was carried out to assess eventual formation damage and the filters efficiency by conducting a series of multiple pressure fall-off tests coupled with injection profile logging to monitor any induced damage within the wellbore region. Finally, the operational aspects and the integration within field development plans were addressed, especially with the recommended well placement and completion. This culminated in a field development strategy for formation damage mitigation in tight carbonate reservoirs during production and injection phase that can be used in other similar fields.
This paper presents an approach for permeability characterization of a thin, high-K dolomitized interval based on application of depositional and diagenetic concepts. The interval is 3.5 feet in average thickness and has higher permeability values than surrounding limestones. It is an important drilling target and the permeability shows significant heterogeneity vertically and laterally which impacts future well placement and completion designs of long laterals. Detailed core observations from 85 wells suggests that the intensity of dolomitization is laterally variable at an inter-well scale, but that there is a clear vertical trend of dolomite content increasing towards the middle part of the interval at each well location. The dolomitization is often concentrated within the grain-dominated facies and, in general, it leads to increased permeability. However, in some instances it can result in an intense overdolomitization yielding degraded reservoir quality. Permeability can also be improved in some areas by leaching of non-dolomitized material, particularly in the crestal area of the field. Core and petrographic observations combined with plug analysis data suggest that the dolomitized zone can be divided into three sublayers and characterized by two rock types: Dolostone with well-developed intercrystalline pores (high-K) and highly overdolomitized dolostone that occur in the middle sublayer.Calcareous dolostone characterized by weaker dolomitization and/or dissolution that are in the upper/lower sublayers. This rock type is also occasionally assigned to the middle sublayer where dolomitization is locally weak. Regression analyses of plug porosity-permeability values are characterized by one regression line for the dolostone rock type, which represent a higher permeability trend (Trend 1) that contrasts the calcareous dolostone rock type (Trend 2). The proposed fine-scale layering scheme and rock typing can be used to model the vertical and lateral petrophysical heterogeneity and permeability contrasts of the high-K dolomitized interval.
As part of the ongoing development of a large offshore oil field, an asset owner places a strong emphasis on continuous improvement of the established framework for integrated post-drill well analysis. The geology of the candidate field is complex and the occurrence and distribution of the extreme permeability features that dictate early water production is highly uncertain. While much effort is devoted to mitigating their adverse impact through proper integration of surveillance data for accurate well planning, post-drill outcomes can still diverge significantly from pre-drill expectations. Several wells have been drilled in the production build-up campaign, including ground-breaking pilots and many more are following in very quick succession as part of the life cycle strategy for the field. Due to high drilling frequency, the challenges of assimilating learnings through conventional post-drill analysis for optimization of future drill wells can be enormous. To apply key lessons from these wells in building quick baseline knowledge for reservoir model update and drill plan optimization, the modeling and development team have developed an improved workflow for integrated post-drill analysis. The workflow leverages the full benefit of collaboration between multi-disciplinary teams to integrate 3D seismic data, multiple well information (including geologic reports, well logs and petrophysical results) and surveillance data from new drill wells to benchmark pre-drill expectations. An important aspect of the approach is the quick incorporation of drilling results into static and dynamic models via a cycled, closed-loop workflow for quick assessment of model fidelity through an evergreen update process. A multifunctional post-drill analysis facilitates critical consideration of well results to capture significant learnings that influence future drill well and data acquisition optimization, reservoir model history match and prediction enhancements, and identification of drilling hazards and geological features that affect reservoir performance. This paper describes the methodology used to plan and implement post-drill well analysis within a fast paced and high drill frequency environment. Key elements of the methodology are described through the use of a case study example, and include: Standardized subsurface workflow, comparison of post-drill well results with pre-drill well expectations, identification and documentation of significant observations and lessons learned improvement of history match & predictive capability of reservoir models and integration with other drill-well delivery processes.
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