The management of produced water has become a main issue in petroleum industry due to the huge quantities to be dealt with. Produced Water Re-Injection (PWRI) allows combining disposal with Improved Oil Recovery (IOR) opportunities. Nevertheless, PWRI could damage the formation, eventually compromising field performances. Well impairment is a complex phenomenon depending on several aspects. This paper focuses on the impact of Oil In Water (OIW) in injectivity performance, validating lab predictions and field evidences. A comprehensive review of field cases has been carried out, analyzing injection well performance with Production Data Analysis (PDA) tools together with water quality data. On a selection of field cases where OIW has been identified as main impairment reason, a workflow was established performing core flooding experiments to measure experimental loss of permeability with different content of OIW. Obtained results have been integrated by bibliographic research. Field evidences showed a direct relationship between permeability reduction and hydrocarbon content; moreover, injectivity impairment measured on field data has been found to be comparable (same order of magnitude) with the permeability reduction measured on core flooding. Combining all data together, a common trend of injectivity reduction vs. OIW content has been extrapolated passing through the definition of Injectivity Index (II). New water injection concept depends on several elements that could affect the overall project value, water quality requirements is one of them. Water quality rule of thumb can be found in literature, but each project basis of design is different. The proposed approach allows to preliminarily quantifying the expected well impairment as function of water quality. It can be used as a first tool to dimension treatment facilities in function of the reduction of injectivity that we can accept for any given reservoir. Obtained trend is representative of a subset of real field cases, where OIW content is the main impacting parameter on PWRI well damage.

3D model is a valuable tool in reservoir management, provided its representativeness of reservoir dynamics.Traditional History Match mainly focuses on reproducing reservoir behavior at well scale. A good match is not always representative of fluid movements in the reservoir. The proposed approach for 3D model validation combines and compares the results of integrated production analysis, in particular flow paths identification, with history matching by using streamlines technology. Streamlines speed up the comparison process especially in complex 3D models. The workflow is based on a massive Production Data Analysis (PDA) where geological and dynamic data are integrated to identify preferential paths followed by the different fluid phases during the producing life of the field. The main result is the Fluid Path Conceptual Model (FPCM) where aquifer and injected water movements are clearly identified. Once the flooded areas are detected, streamlines are traced on the history matched model in order to easily compare the simulated connections with hard information from PDA. Actions to improve the model representativeness are suggested and integrated in an iterative tuning process. This paper presents the results of the methodology applied on two complex fields with different injection strategies. FPCMs resulting from PDA provided a powerful boost to drive the history match and speed up the whole process. Priority was given in reproducing the identified preferential paths rather than to perfectly match well production data (which can be also affected by allocation uncertainties) by means of local unrealistic adjustments. Streamlines were run on Intersect simulation, proving to be a fast and powerful tool for the visualization and understanding of fluid movements in the 3D Model. Since streamlines are used as visualization tool and are traced on a corner point geometry grid using fluxes provided by reservoir simulation, the reliability of the simulation output is preserved. Once the model is representative of the real field behavior, it can be used as predictive tool in Reservoir Management to optimize the current injection strategy, promoting most efficient injectors.

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Oil companies are focused on asset value maximization with a view to augment overall hydrocarbon recovery. This goal remains a notable challenge to execute in mature fields which contribute to majority of the world's global oil production today. An integrated structured approach from the multidisciplinary skill set is the key for redeveloping mature fields.The present paper focus on the efforts spent on a brown oil field located approximately 35 km offshore in a water depth of 90 m with more than 35 years of production. To date the field is in production with 8,000 bopd and a 85% watercut.The concession License expiration and the facilities ageing/deterioration forced a technical reevaluation of the possible development scenarios for the field with the aim to maximize the recoverable reserves and minimize the capital expenses.Based on high level of synergy amongst the teams and thanks to the workflow adopted, the identification of "still recoverable" under-drained potential has resulted in leading to a new development phase in the mature asset.The paper will cover the full spectrum of static and dynamic review including well location placement/ trajectory/completion design, artificial lift requirements, reservoir pressure support needs, evaluation of tertiary recovery schemes while keeping into account economic feasibility together with Concession License expiration. Results and conclusions together with lessons learnt that can be applied to similar assets globally will also be presented.

Rejuvenation of mature assets plays a crucial role in current low oil price scenario, allowing improving production with limited investments and risks. Nevertheless, brown field rejuvenation is often very demanding in terms of complex integrated reservoir studies, mainly due to the huge mass, heterogeneity and reliability of available data. In this context, it is crucial to shortly identify the key parameters that allow to robustly detect the main flow paths in the reservoir, their current status and any possible optimization. An integrated workflow is proposed for brown fields where oil production is mainly driven by water injection. Produced water salinity plays a key role, acting as natural tracer whenever a huge contrast in salinity exists between formation and injected water. Production and geological data throughout all the different field deployment phases are deeply integrated. The outcomes are conceptual models where the evolution of fluid paths in time is clearly identified, providing a valuable support for both validating the geological vision of the reservoir and driving the dynamic model history match. Once the 3D model is available, streamline analysis is performed to verify its robustness, compute the efficiency of the current injection scheme and drive the deployment strategy optimization. This paper is focused on a mature Egyptian field characterized by an extremely complex heterogeneity, more than 60 years of production and about 500 wells drilled. The field is undergoing a rejuvenation process including water injection optimization and chemical EOR. Despite the amount of data, some uncertainty in the field behavior is still present, mainly due to the high impact of commingle production. Due to ESP well completions and similar oil characteristics in all layers, both PLTs and geochemical analysis could provide only a marginal support to the analysis. In this context, the proposed workflow allowed detecting the main connections without any additional data collection, thus reducing costs and timing. The results of the analysis improved the understanding of some critical aspects both on static and dynamic sides: validation of fluid contacts, well integrity issues, aquifer support, faults impact and commingle contributions. The results achieved show that in a framework characterized by the presence of a huge number of measured data, a systematic approach for their analysis and interpretation can help in extrapolating the main fluid paths from the complexity of brown reservoirs and thus providing a valuable support to speed up and optimize fields analysis and rejuvenation.