A chemical EOR project has been implemented in the fluvial succession of the Rayoso Formation since 2014. In the aim to understand polymer flooding processes, geological 3D modelling and numerical simulation are powerful tools to interpret field data and help to mitigate uncertainties of an early polymer injection at field scale. The Rayoso Formation was modeled following a multi-scale rationale: a multi-field scale model (>50km), a field-scale model (>10km) and a pilot-scale model (>1km). The results of numerical simulations were compared with the observed field? data. These runs included polymer injection vs. water injection, multiple adsorption values and polymer degradation. The key results of that work are summarized as following: For polymer injection the simulation reproduces the increasing oil cut in the observed data, whereas the waterflooding cases show an oil cut drop. Polymer simulation also matches the observed bottom hole pressure drops in producers better than water simulation. Based on these results, it has been possible to determine the polymer response.Analytical calculations, based on tracer arrival time, give a polymer adsorption greater than 300 µg/g. Using different values of adsorption, the simulation shows that the actual value is one magnitude order less than the calculated one. Therefore, extremely high values of adsorption are excluded.Significant degradation is ruled out by running a simulation with a polymer viscosity 4 times smaller than the non-degraded one at the same concentration. The simulation shows an early arrival of the degraded (less viscous) polymer at the producer wells. This has never been observed in the wells showing that the degredation has a negligible effect. Numerical simulation is thus used to interpret the polymer pilot results and consequently, allows to mitigate risks and make early decisions.

The case study here presented supports the on-going EOR development project of a low net-to-gross fluvial system producing viscous oil form a thick sedimentary column in San Jorge Gulf Basin, Argentina. The selected strategy consists in combining dynamic modeling, analytic tools and field measurements to assess field potential and to model uncertainty through different yet plausible deterministic scenarios. The selected area is Los Perales field in Southern Argentina, with 2880 wells producing from more than 1000 m thick column of thin fluvial sandstone bodies and tuffaceous shale floodplain intercalations. This is a mature field extensively drilled, although single sand extension is likely to be below well spacing. Sands are captured by well logs but have no seismic representation, making connectivity prediction in between wells critical for any IOR or EOR project. For this reason, sand lateral connectivity is estimated by statistical tools, and then several plausible 3D connectivity scenarios are used to model geological uncertainty. Simple analytical tools support simulation results on the identification of key dynamic factors affecting polymer flood incremental volumes. Nevertheless, different modeling approaches are here combined to build deterministic scenarios such as fine scale 2D section models and different resolution 3D sector models for different purposes. We estimate that, given the adverse mobility ratio, when 45% water saturation is reached in the reservoir water sweep efficiency becomes so dramatically low that almost no oil is pushed and water cut raises over 95% as historical production data shows during the 25-year water-flood history in the field. The resulting low recovery factor presents a huge opportunity for polymer flood not only in the already swept areas and heterogeneous regions but also in some unproduced layers with water forecast on swabbing tests. A zone-ranking based on a vertical proportion curve for reservoir and non-reservoir intervals allows us to narrow the development to lower risk confined regions. Further investigation and detail modelling in these regions permit us to assess uncertainty and estimate incremental volumes as up to 3 times those recovered by water-flooding. Production logging confirmed the relevance of targeted intervals in well production, hence supporting polymer business case. This methodology is used to forecast, rank and select the best areas for polymer flood. This integrated approach combines geology, petrophysics and engineering using several laboratory tests, multiple deterministic scenarios and statistical tools to analyze polymer flood opportunities in a large field producing from a low net-to-gross thick sedimentary column.

This work shows the realization of a 3D static and dynamic model with feasibility analysis and conceptual planning in the field of "La Itala" in Los Perales. Incorporate in one unique project feasibility and conceptual model is the principal benefits of this method because until now we haven't this kind of project in this all field. To perform this project, it was used some basic data of the wells, like SP and resistivity and a petrophysical model. To do the feasibility analysis we use wells basics curves envelops. Combining with core analysis a static facies model was generated. Using averages of rock and fluid parameters along with the history of production and injection, a dynamic model was initialized. This model permits to do a "History Match" at field level. This allowed visualizing the evolution in time of displacement of fluids, product of the water injection. The conclusions of this model define continuity with the conceptual model using a complete petrophysical study (VCL-Phie and Sw). Combination of the results of SP and short resistivity envelopes yielded to a first approximation of a Vclay. From there a binary log was generated. Settle the same curve with a vertical proportion curve; reference levels used to separate the model in zones were defined. The study of cores fostered a relationship between facies and resistivity. To make a reliable 3D structural model the control was made by some surfaces created on well tops by correlation. In this static model were charged all wells data available (perforations, facilities, production and injection). Along with rock properties and fluid average, the model was initialized. At this stage of visualization, a quick historical setting, at field level, injection and production served to understand the behavior of fluids in the reservoir. This understanding in the changes of water saturation turns to be a very important input for the next phase of conceptualization. Having a static and dynamic visualization model purchase in both ways the conceptualization phase, whether or not pass to the next stage. Everything done in the first stage is the starting point of the next (Front End Loading - FEL). The FEL methodology is deeply rooted in the DNA of YPF. In this case, with software who allowed enhancing this work process, creating a unique project where all available parameters are incorporated, with the possibility of being used in the different phases of the study. At the same time, each analysis on the project, adds value to the next step. This work allowed to reservoir engineer of this field to improve the oil recuperation factor.

The current low oil price scenario makes it increasingly critical to build robust business cases, to model uncertainty and to identify the most efficient and economically viable scenarios for any field development or redevelopment strategy. The purpose of this paper is to present a multi-scale reservoir modelling approach to assess economic viability for the development of an EOR project in an adverse oil price scenario. We present an on-going polymer injection project in a brown oil field in the Western Flank of the Golfo San Jorge Basin in southern Argentina as case study for this methodology. Productive interval consists of a 1000 meters-thick low net-to-gross fluvial succession, in the Cretaceous Bajo Barreal Formation. The field produces a ~100 cp oil with very low recovery factor and a watercut of 94%, after 25 years of waterflood. The need for high resolution models is validated by a cell size sensitivity analysis on polymer injection simulations. We verified that almost 50% error on oil incremental forecasts by polymer injection is obtained if 50 × 50 m cells were used. Therefore, combining purpose-built dynamic models in different scales and economic evaluation we support the on-going execution of the EOR pilot project. Several static/dynamic models are built at different scales (from 10 km to 100 m) to capture depositional trends and model stratigraphic and sedimentary heterogeneities. We evaluate different physical aspects of the polymer injection process with specifically designed numerical simulations at appropriate resolution. We think that detailed modelling and data acquisition are highly profitable decisions even in current challenging economic scenario, aiming at reducing uncertainty and strengthening business cases. Indeed, laboratory and field measurements, identification of critical variables, and high resolution modelling proved to reduce forecast uncertainty and strengthen business case economic indicators.