Enhancing Asset Profitability with Flexibility for Life Cycle Field Development – A Comparative Study for Well Placement Allocation and Platform Capacity

In the context of rising global energy demands that are aligned with sustainable energy supply, making informed decisions regarding investments has become increasingly complex. This complexity is particularly challenging in oil and gas management, where devising a production strategy and commencing field development pose challenges given the multitude of uncertain variables and extended timelines involved. Flexibility is key to address these uncertainties. Hence, the objective of this article is to evaluate the importance and advantages of considering the expected value of flexibility in the decision-making process to create a strategy able to deal with the risks imposed in the petroleum industry. Doing so, this article provides an examination of different approaches employed for the implementation of flexibility, considering the well placement allocations, final strategy selection, and platform capacity, thereby offering an informed perspective on this crucial aspect of reservoir strategic management.

The methodology for the construction of a flexible strategy employs theories in decision analysis combined with reservoir simulation models and optimization methods in a Bayesian probabilistic approach to access the expected value of the flexibility (EVoF). We present a structured technique to assess and select optimal strategies, specifically focusing on managing uncertainty in the initial stages of field development to identify potential platform capacities and drilling location strategies in the face of uncertainties related to reservoir characteristics, facility operations, and market conditions. To illustrate the results, we conduct a case study on an offshore benchmark field with Brazilian pre-salt features under WAG-CO2 recovery method, involving the complete reinjection of produced CO2 to mitigate greenhouse gas effects.

The results reveal that the initial strategy can highly impact the final net present value outcome and risk curves due to the first wells drilled. The results also indicate that increasing flexibility in the early stage of development could extract the best results related to financial return. Our study underscores the immense potential of integrating flexibility valuation and uncertainty quantification into the energy planning and policy-making process. It also highlights that the holistic integration between flexibility and reservoir simulation facilitates the identification of innovative investment strategies and enhances the decision-making process with the tools to navigate the complexities of uncertainty with greater confidence and adaptability.

This innovative approach offers a structured technique that not only addresses uncertainties in the subsurface reservoir and economic scenarios but also contributes to the identification of methodologies for investment management, enhancing the adaptability in the dynamic landscape of reservoir engineering.

Integrated Multi-Scale Pore Characterization of Carbonate Rocks in the Barra Velha Formation, Santos Basin, Brazil

Carbonate rocks feature heterogeneous porous systems that span multiple scales, from pore level to the reservoir scale. The complexity and diversity of carbonate reservoirs demand a consistent approach to their characterization. The efficient integration of multiscale imaging data and petrophysical data is increasingly important to address the challenges associated with these complex carbonate reservoirs. A crucial step in overcoming these scale gaps in reservoir modeling and simulation involves enhancing the characterization of reservoir flow units and their associations with geological and petrophysical heterogeneities at varying scales. In this study, we focus on the classification of pore types using digital rock analysis and petrophysical evaluation of pre-salt lacustrine carbonates from the Barra Velha Formation (BVF) in the Santos Basin using computerized tomography (CT), core samples description, and petrography. Eight types of pores were identified at the core scale: interparticle, stratiform-vuggy, growth framework, vuggy, vuggy-fracture, fracture, interclast, and intraclast. The distribution and characteristics of these pore types were analyzed at different scales, including thin-sections and micro-CT, and nuclear magnetic resonance (NMR), which highlights the diversity in the porous system and the impact of different pore types on porosity and permeability. NMR analyses illustrated the pore size heterogeneity to provide distinction between tight and porous samples. Hydraulic rock units (HRUs) were defined based on flow zone indicator (FZI) using the probability plot approach. Seven HRUs were defined: HRU1 and HRU2 represent samples with the highest FZI and rock quality index (RQI) values, whereas HRU3 and HRU4 denote intermediate values. HRU5, HRU6, and HRU7 represent units with the lowest values. HRU1 and HRU2 were predominantly associated with vuggy, growth framework, and interparticle porosities, which are often enhanced by dissolution processes. Conversely, HRUs with reduced reservoir qualities (5, 6, and 7), characterized by the lowest permeability values, are more prevalent in intervals with higher silicification and silica and dolomite cementation, presenting a variety of pore types at a macroscale. The integration of multiscale imaging techniques and petrophysical data underscores the complexity of pore systems, providing crucial insights into their reservoir characteristics.

Construction of Single-Porosity and Single-Permeability Models as Low-Fidelity Alternative to Represent Fractured Carbonate Reservoirs Subject to WAG-CO2 Injection Under Uncertainty

Fractured carbonate reservoirs are typically modeled in a system of dual-porosity and dual-permeability (DP/DP), where fractures, vugs, karsts and rock matrix are represented in different domains. The DP/DP modeling allows for a more accurate reservoir description but implies a higher computational cost than
the single-porosity and single-permeability (SP/SP) approach. The time may be a limitation for cases that require many simulations, such as production optimization under uncertainty. This computational cost is more challenging when we couple DPDP models with compositional fluid models, such as in the case of fractured light-oil reservoirs where the production strategy accounts for water-alternating-gas (WAG) injection. In this context, low fidelity models (LFM) can be an interesting alternative for initial studies. This work shows the potential of compositional single-porosity and single-permeability models based on pseudo-properties (SP/SP-P) as LFM applied to a fractured benchmark carbonate reservoir, subject to WAG- CO2 injection and gas recycle. Two workflows are proposed to assist the construction of SP-P models for studies based on (i) nominal approach and (ii) probabilistic approach of reservoir properties. Both workflows begin with a parametrization step, in which the pseudo-properties are optimized for a base case in order to minimize the mismatch between forecasts of the SP/SP-P and DP/DP models. The new parametrization methods proposed in this work showed to be viable for the construction of the SP/SP-P models. For studies under uncertainties, the workflow proposes obtaining pseudo-properties by robust optimizations based on representative models from a DP/DP ensemble, which proved to be an effective method. The case study is the benchmark UNISIM-II-D-CO with an ensemble of 197 DP/DP models and two different production strategies. The risk curves for production, injection and economic indicators obtained from DP/DP and SP/SP-P ensembles showed good match and the computational time spent on simulations of the SP/SP-P ensemble was 81% faster than DP/DP models, on average. Finally, the responses obtained from both ensembles were validated in a reference model (UNISIM-II-R) that represents the true response and is not part of the ensemble. The results indicate the SP/SP-P modeling as a good LFM for preliminary assessments of highly time-consuming studies. Besides, the workflows proposed in this work can be very useful for assisting the construction of SP/SP-P models for different case studies. However, we recommend the use of the high-fidelity models to support the final decision.