Selection of Optimum Completion Intervals Based on NMR Calibrated Lithofacies

Lafournère, Jean-Paul; Dutan, Jorge; Hurtado, Jorge Luis; Suter, A.; Bringer, F.; Naranjo, Michelle; Bourge, Jean-Pierre; Gozalbo, E.

doi:10.2118/169372-ms

Cited by 4 publications

(1 citation statement)

References 5 publications

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“…They are based on the integration of core description and core analysis (SCAL) making the grouping shown in Fig. 8 consistent across disciplines from depositional environments to plug measurements and production ranges (Lafournère et al 2014). The propagation to the well is based on Winland methodology (Kolodzie, 1980).…”

Section: Field Case: Shushufindi Ecuadormentioning

confidence: 99%

A Tuning Strategy to Align Static and Dynamic Modelling

Bourge

Bolanos

Lafournère

et al. 2015

SPE Latin American and Caribbean Petroleum Engineering Conference

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The main aim of geological modeling is to include all available data, such as seismic data, well logs, and core data, and to combine these data with more descriptive information, such as the geoscientist's understanding of the conceptual geological model and their experiences in similar environments, to predict the reservoir properties between the wells. However, in many cases, when the static model is passed to the reservoir engineer for history matching, the detailed geological knowledge and uncertainty is not fully utilized. This can lead to a model that may match the production data but actually has very little predictive power.Depositional maps provide very useful constraints on model building. By giving a visual representation of the geological context, they can incorporate well and seismic information and the dynamic characteristics recognized from the production data, tracer information in cases of water injection, and pressure information. However, there always remains a degree of uncertainty with respect to the geometries and orientations of the geobodies, so the tuning of the maps is, by definition, an iterative process. This coupling between static and dynamic modeling is critical to achieve true discipline integration, aiming to retain the key information from each domain. This paper presents an iterative technique to update these depositional maps in the areas of uncertainty between the wells. The required changes to honor production data and reservoir pressure trends during the history match are translated into facies modifications that are validated in terms of being consistent with both the control well data and with the conceptual depositional model. This methodology was applied to the modeling of Shushufindi field, Ecuador. The long-term field development plan is being guided by a fine-scaled geocellular model that was designed to capture the geology at a high resolution. The workflow adopted required the collaborative efforts of the geology, geophysics, petrophysics, and reservoir engineering team members throughout the entire process.

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Section: Field Case: Shushufindi Ecuadormentioning

confidence: 99%

A Tuning Strategy to Align Static and Dynamic Modelling

Bourge

Bolanos

Lafournère

et al. 2015

SPE Latin American and Caribbean Petroleum Engineering Conference

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New Opportunities Identification Workflow, Pañacocha Field, Oriente Basin, Ecuador

Guerrero

Vega

Alvarez

et al. 2015

SPE Latin American and Caribbean Petroleum Engineering Conference

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Over the years, simulation models have been helping oil companies and stakeholders to make investment decisions. However, these models are not always available to help with the field development planning. A fast and efficient workflow performed for the identification of new opportunities in the Pañacocha field is presented. To start the workflow, a conceptual geological model was identified for each reservoir, based on the available data and nearby analog fields. Quality control, updating and reinterpretation of well top data, petrophysical parameters maps (net pay, porosity, and water saturation), and original oil in place estimations were carried out to identify untouched areas. A total of 45 locations that may still contain oil were identified. For the next step, a decline curve analysis was carried out, and well type curves were generated to determine the estimated ultimate reserves (EUR), drainage area, and recovery factor by well. The range of recoverable oil associated with each location was estimated by varying all the parameters involved in the volumetric formula. Finally, the locations were ranked based on their production potential. The selection of drilling targets included the associated geological and operational risk. A base case, based on the contract minimum commitments, is presented. However, this study shows that a more aggressive drilling campaign is possible. In conclusion, this workflow allowed us to have a better understanding of the field potential. Oil in place volumes and recovery factors were updated. Analysis of produced fluids helped to assess reservoir performance. The economic analysis following this study will help in selecting the best option to develop the field.

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Producing the Limit, by Re-Defining the Rock Typing Classification in a Mature Oilfield: Case Study in the Auca Field, Oriente Basin, Ecuador

Morales

Lafournère

Bringer

et al. 2017

Day 2 Thu, March 16, 2017

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The Auca field is located in the northern Oriente basin (Ecuador) with hydrocarbon production coming from Cretaceous fluvio-estuarine and shallow marine sandstones. The field has produced more than 547 million barrels of oil since 1972 and by the end of 2015 the field recovery factor was approximately 14%. In December 2015, the reservoir management and the field re-development activities for the Auca field were awarded to Schlumberger Production Management (SPM) under the name of Shaya project. Since then, to sustain the field re-development activities, an integrated reservoir characterization process has been implemented. In this depositional environment reservoir evaluation can be very challenging, especially when using only conventional well logs. It is proposed in this paper that the acquisition of texture dependent measurements is the solution to improve the understanding of the reservoir rocks in highly heterogeneous environments. Based on our experience in Ecuador, incorporating nuclear magnetic resonance (NMR) in the petrophysical model appears to be the best way to collect the needed texture dependent data. The Rock type characterization in the field was based on mercury injection capillary pressure data. This method enables the determination of pore throat profiles for each rock type and the dominant interconnected pore system, which corresponds to a mercury saturation of 35% in a capillary pressure curve. An empirical relationship was used to relate conventional porosity and permeability to pore throat profiles, and this was used to classify rock types. With the purpose of validating reserves and optimizing the field development plan, a model based on rock type characterization was developed using existing core, log and production data. Additionally, this model was calibrated using data from multiple fields in the basin. The propagation of the model from core to logs was accomplished through a relationship between gamma ray, density, neutron and NMR logs with core porosity and permeability in key wells. These relationships are dependent on rock type, and they were used to extrapolate core characterization to those wells without cores. Maps of rock type distribution were used to classify areas according to their petrophysical properties. These maps were also used to delineate the reservoir limits, helping to validate and identify prospective areas for future drilling and workovers. This paper presents the characterization of the reservoir into rock types by integrating geological, petrophysical and production data through Neural Network Analysis, establishing a fundamental input into and support for the development of the exploitation plan.

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Selection of Optimum Completion Intervals Based on NMR Calibrated Lithofacies

Cited by 4 publications

References 5 publications

A Tuning Strategy to Align Static and Dynamic Modelling

A Tuning Strategy to Align Static and Dynamic Modelling

New Opportunities Identification Workflow, Pañacocha Field, Oriente Basin, Ecuador

Producing the Limit, by Re-Defining the Rock Typing Classification in a Mature Oilfield: Case Study in the Auca Field, Oriente Basin, Ecuador

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