Reservoir 2 shows the same vertical facies stacking pattern across Oilfield A. These facies are observed to be laterally continuous across other oilfields in Abu Dhabi. Multi-scale static and dynamic data show a north to south degradation in reservoir quality across the field. A petrographic, core and borehole image-based evaluation has generated a robust geological concept governing porosity and permeability distribution across Reservoir 2 that is calibrated to seismic impedance and dynamic data. Diagenetic phases were quantified and mapped as part of a detailed sedimentological and petrographic description of Reservoir 2. Samples were analysed for stable isotopes and fluid inclusion microscopy. Chemical compaction features were described in detail in high quality cores. The cored intervals feature abundant preserved samples with up to 30% of the cored interval unavailable for reservoir characterization due to preservation. Consequently, a detailed borehole image description was undertaken and utilized to describe the structural features at log scale and fill in the missing core sample gaps. Petrographic description and mapping shows calcite cement occludes almost all macroporosity in the south of Reservoir 2. The abundance of cement decreases towards the north. Core and BHI based descriptions of chemical compaction features show a higher abundance of stylolites in the south Reservoir 2 than in the north. Most of the primary fluid inclusions trapped within calcite cements are monophase, potential evidence that pore-filling calcite started to precipitate under cooler burial conditions, at temperatures between 60-70°C. It is proposed that stylolitisation is contemporaneous with cementation where carbonate material dissolved during chemical compaction formed the main source for cement precipitation. Reservoir 2 is up to 10% thinner in the south of Oilfield A than in the north. Increased chemical compaction in the south is correlated with decreased reservoir thickness. There is a strong correlation between the pattern of reservoir thickness and P-impedance from seismic inversion. P-impedance is negatively correlated to porosity. Stylolites are most common in reservoir intervals 2A and 2B. These intervals display a wide range of porosity and permeability from north to south, while in contrast reservoir interval 2C, with very few stylolites, has a narrow range of porosity and permeability variation field wide. It is proposed that chemical compaction is the key driver for degrading reservoir quality in Reservoir 2. All scales of static and dynamic data have been reconciled to show that chemical compaction, cementation and reservoir quality are intimately related processes. The implications for producer and injector well design are significant. Depending on the location of the planned well and the development interval to be drilled, well spacing and reservoir contact should vary accordingly, while maintaining the optimal field development pattern.

This paper identifies re-stimulation opportunities in existing horizontal wells with existing multistage hydraulic fracturing to increase oil production in a tight carbonate formation, offshore Black Sea. Pilot candidates were screened and ranked through the following decision criteria described in this paper, coupling reservoir, production and completion parameters. Favorable pilot candidates were verified by numerical simulation, which also highlighted potential areas of by-passed oil for future sidetracks. In an era of low oil prices, it is increasingly difficult to justify drilling new wells, especially in the offshore environment. A strategic shift towards revamping and workovers has made operators of tight and unconventional reservoirs to focus on restimulation. Many factors define success herein, and the key to finding the right candidates. Synergy between numerous parameters, combined often in indexes or drivers by their nature, is used to score and prioritize existing well potential and associated risks. On the other hand, reservoir and its understanding still play a major role and prevail over solely statistical methods. Top scoring refracturing candidates in this work were simulated in both full field and sector models. Real post-job fracture geometries and newly initiated fractures were critical inputs into unstructured reservoir simulation grids to ensure that the identified targets of the restimulation pilot wells are realistic and achievable. Recent multistage stimulation jobs in this field accidentally led to several "frac hits" (cross-well communication initiated while pumping a hydraulic fracturing treatment), which were confirmed by tracer analysis in the adjacent wells. Subsequent offset well behavior had both positive and negative effects, thus enabling the quantification of gains from restimulation, where possible, and intrinsic well interference. The choice between refracturing old or new wells, and finding the balance were the major pitfalls in this work. Wells, drilled 5-7 years ago and stimulated with typically 3 stages, had sub-optimal completions for refracturing, however were placed in the better quality rock, therefore displayed higher initial production. Delineating the reservoir bodies from seismic inversion and integrating with the simulation model, highlighted favorable well placements and historically it was proven to reduce initial water cut by 2-3 times. Recent and more extended wells were positioned in the tighter, "saddle" zones, drilled and completed couple of years ago. They had due drawdown management, flatter decline, plus less mechanical and operational risks. Pay in these extended wells was recognized as a major uncertainty when history matching flowing bottomhole pressures. Results of the statistical scoring and decision criteria, to enable selection of refracturing candidates, are presented in this work, along with the integration and coupling these outcomes with the applied reservoir simulation. Both sets of results were used to find new opportunities for the mature field redevelopment.

A well log based reservoir study together with post stack 3D seismic data analysis was used to assess the petrophysical rock type distribution in an area located on the West side of Lake Maracaibo-Venezuela. The calculated petrophysical rock types were obtained using the Windland R35 (Gunter, et al, 1997) equation which includes information collected from core data: pore throat size distribution, porosity, and permeability. Permeability and rock type curves at the non-cored wells were predicted using available core data. Several consistency checks and quality control revisions were applied to obtain the results from these predictions in order to have a reliable relationship between petrophysical properties and petrophysical rock types. The resulting curves at the depth interval of interest were correlated throughout the field and calibrated with 3D seismic data. In order to obtain the correct parameter to enhance spatial rock type distribution, seismic attribute analysis was performed and a well log vs. seismic attribute cross-plot relationship was established to predict petrophysical rock properties in the interval. The predicted petrophysical rock type map provides extremely valuable constraints for the development of the field. The results clearly indicate that the application of this workflow is valuable for determining new locations to be drilled either for production or injection.

To establish relationships between seismic derived acoustic impedance and LWD porosity measurements from several horizontal wells to be implemented into property modeling. This workflow is a sequential process that integrates property relationships from seismic scale to log scale using log data from a dozen of vertical wells and validate results at field scale with log data from about 50 horizontal wells. Overall process functions at grid-block scale in a 100x100mx1ft cell size following the four main phases. The first phase, involves exploratory data analysis and quality check. This is followed by a second phase of model building to concatenate all the required modeling steps. Third phase of model optimization explores the effect of all the parameters and data links defined in the process. Finally fourth phase involves validation to assess residual errors from the resulting porosity distributions and quantifying predictability of the model itself. A comprehensive and robust set of properties is generated by performing a recursive and convergent process of property modeling using lateral coverage from seismic inversion products and vertical resolution near well log scale. Independent analysis of different scales of porosity measurements are reconciled in this systematic approach by defining average distributions and descriptive statistics of reservoir properties at field scale. Variable data types, sample sizes and data resolution evolves across four different phases that integrates a holistic understanding of datasets in different dimensions. Quantitative analysis of seismic data ultimate correlates to a dense dataset from long horizontal wells. Final predictability of the model reaches a high confidence level (about 80% accuracy) when testing the predicted properties vs real measurements in about 50 horizontal wells. Multiple realizations of properties distribution matching all the available data is final output that provides a better understanding of reservoir property. This workflow allows total utilization of log data from horizontal wells into property distribution with no impact on overall statistics. No complex de-clustering operations are required as all the descriptive statistics are defined from vertical wells calibrated to core and seismic data. This methodology maximizes the value of LWD formation evaluation logs in property distribution, by combining the resolution of the logs along long horizontal wells with the strong lateral coverage of seismic inversion cubes.

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