Hydraulic fracturing is being widely employed to augment wells’ productivity, thus facilitating proper depletion of the reservoir fluids and adding to the recoverable hydrocarbon reserves. The benefits of hydraulic fracturing are particularly pronounced in reservoirs exhibiting low permeability, high skin and, in case of gas condensate reservoirs, near wellbore condensate banking. A gas condensate field, code name ‘Delta’, has been producing from sandstone reservoirs for the last two decades. Most of the wells have been suffering from low productivity primarily due to a relatively low reservoir permeability (0.5 to 10mD) and high drilling induced skin. The problem has become more pronounced with the depletion of reservoir pressure resulting in condensate drop out around the wellbore. This paper details the envisioned economic incentives and the post-frac deliverability results from the recent hydraulic fracturing campaign carried out in a gas condensate field. The paper highlights the operational challenges encountered and the evolution of the hydraulic fracturing treatment design, execution and post-frac completion / flow-back strategy based on our experiences that contributed towards a successful and challenging campaign.

Defining the flow and distribution of fluids in porous media has always been of key importance in modeling and predicting the performance of oil and gas reservoirs. Based upon the rock-fluid interactions, reservoir rocks have to be classified into separate flow units called rock types. This task is particularly complex in carbonates as they are generally impacted by diagenesis and cannot be represented by a single porosity permeability relationship per litho-facie. Establishing accurate rock types in carbonates, therefore, requires integration of various petrophysical data with the available rock, fluid and geological information. Various techniques have evolved in the industry for formulating rock-types (Pittman, RQI, FZI, Lucia, Winland, etc.), each technique offering its benefit depending on the nature and variety of data available. This paper presents a newly adopted workflow to formulate an RRT definition for a carbonate reservoir by integrating data from MICP, CCA, petrophysical logs and lithofacies information. The workflow involves associating the pore throat size distribution evaluated using MICP data with the measured porosity and permeability values utilizing the Winland R35 equation. Hydraulic flow units are identified using the Stratigraphic Lorenz Plot, based on the change of flow and storage capacity slopes. Pc, PTR, Phi and K discriminators were established and were used to as cut-offs for defining intervals representing good and poor facies. The new methodology helped to achieve a very good match (>80%) of water saturation from the initialized model with the log derived saturations in all wells drilled thus far in Reservoir-A. The methodology further helped optimize the number of effective rock types required to effectively delineate the field dynamic characteristics, helping reduce run time and anticipated convergence issues.

The aim of this study is to demonstrate the value of an integrated ensemble-based modeling approach for multiple reservoirs of varying complexity. Three different carbonate reservoirs are selected with varying challenges to showcase the flexibility of the approach to subsurface teams. Modeling uncertainties are included in both static and dynamic domains and valuable insights are attained in a short reservoir modeling cycle time. Integrated workflows are established with guidance from multi-disciplinary teams to incorporate recommended static and dynamic modeling processes in parallel to overcome the modeling challenges of the individual reservoirs. Challenges such as zonal communication, presence of baffles, high permeability streaks, communication from neighboring fields, water saturation modeling uncertainties, relative permeability with hysteresis, fluid contact depth shift etc. are considered when accounting for uncertainties. All the uncertainties in sedimentology, structure and dynamic reservoir parameters are set through common dialogue and collaboration between subsurface teams to ensure that modeling best practices are adhered to. Adaptive pluri-Gaussian simulation is used for facies modeling and uncertainties are propagated in the dynamic response of the geologically plausible ensembles. These equiprobable models are then history-matched simultaneously using an ensemble-based conditioning tool to match the available observed field production data within a specified tolerance; with each reservoir ranging in number of wells, number of grid cells and production history. This approach results in a significantly reduced modeling cycle time compared to the traditional approach, regardless of the inherent complexity of the reservoir, while giving better history-matched models that are honoring the geology and correlations in input data. These models are created with only enough detail level as per the modeling objectives, leaving more time to extract insights from the ensemble of models. Uncertainties in data, from various domains, are not isolated there, but rather propagated throughout, as these might have an important role in another domain, or in the total response uncertainty. Similarly, the approach encourages a collaborative effort in reservoir modeling and fosters trust between geo-scientists and engineers, ascertaining that models remain consistent across all subsurface domains. It allows for the flexibility to incorporate modeling practices fit for individual reservoirs. Moreover, analysis of the history-matched ensemble shows added insights to the reservoirs such as the location and possible extent of features like high permeability streaks and baffles that are not explicitly modeled in the process initially. Forecast strategies further run on these ensembles of equiprobable models, capture realistic uncertainties in dynamic responses which can help make informed reservoir management decisions. The integrated ensemble-based modeling approach is successfully applied on three different reservoir cases, with different levels of complexity. The fast-tracked process from model building to decision making enabled rapid insights for all domains involved.

The aim of this study is to demonstrate the value of a fully integrated ensemble-based modeling approach for an onshore field in Abu Dhabi. Model uncertainties are included in both static and dynamic domains and valuable insights are achieved in record time of nine-weeks with very promising results. Workflows are established to honor the recommended static and dynamic modeling processes suited to the complexity of the field. Realistic sedimentological, structural and dynamic reservoir parameter uncertainties are identified and propagated to obtain realistic variability in the reservoir simulator response. These integrated workflows are used to generate an ensemble of equi-probable reservoir models. All realizations in the ensemble are then history-matched simultaneously before carrying out the production predictions using the entire ensemble. Analysis of the updates made during the history-matching process demonstrates valuable insights to the reservoir such as the presence of enhanced permeability streaks. These represent a challenge in the explicit modeling process due to the complex responses on the well log profiles. However, results analysis of the history matched ensemble shows that the location of high permeability updates generated by the history matching process is consistent with geological observations of enhanced permeability streaks in cores and the sequence stratigraphic framework. Additionally, post processing of available PLT data as a blind test show trends of fluid flow along horizontal wells are well captured, increasing confidence in the geologic consistency of the ensemble of models. This modeling approach provides an ensemble of history- matched reservoir models having an excellent match for both field and individual wells’ observed field production data. Furthermore, with the recommended modeling workflows, the generated models are geologically consistent and honor inherent correlations in the input data. Forecast of this ensemble of models enables realistic uncertainties in dynamic responses to be quantified, providing insights for informed reservoir management decisions and risk mitigation. Analysis of forecasted ensemble dynamic responses help evaluating performance of existing infill targets and delineate new infill targets while understanding the associated risks under both static and dynamic uncertainty. Repeatable workflows allow incorporation of new data in a robust manner and accelerates time from model building to decision making.

A fracturing campaign was carried out in Adhi Gas Condensate Field to improve deliverability from selected low productivity wells, some suspected to be suffering from condensate banking. Tobra interval of Adhi12(T/K), the deepest well in the pop up structure, was hydraulically fractured successfully by placing 133,000 lbs of proppant into the formation. Well flow back was conducted yielding disappointing results contrary to the offset well experiences in the field. Despite extensive and continuous nitrogen lifting, the well produced at minimal liquid rates (50bbl/Day) with very high BS&W (80 - 90%). Polymer (Kill/Frac Fluids) induced fracture/formation damage, calcium carbonate pills (LCM) and deposition of organic scales inducing damage and a possible water block were suspected as likely factors restricting the well potential. This paper presents the investigative work, planning and implementation of a remedial treatment that helped successfully revive production from Adhi-12(T/K) Tobra, a well which failed to deliver the anticipated post frac potential. Aromatic Solvents, used in combination with concentrated organic acid and mutual solvents served to create a strong hydrophilic environment in the, now stimulated, critical matrix. Post remedial treatment production from the well resulted in up to 350 BBL/Day of fluids producing at ~60% BS&W. Nature and volume of the high percentage water however proves to be a concern. No Hydrocarbon-Water Contact at the two reservoir levels has yet been encountered in the field.