Alvaro Talavera

Talavera A. Geological Modeling of Subsurface for Drilling Purposes using Neural Networks and Fuzzy Logic. VI Brazilian Symposium of Rock Mechanic 2014.

Geological-Geomechanical Modeling as a Support for the Design and Monitoring of Oil Wells

Well design and drilling strategy planning are critical steps during exploration and development of oil and gas fields, but the workflow for well design usually follows a simplified methodology that generally focuses on only one or on a few correlation wells. 3D models are only available for, and focused on, reservoir volume prediction and fluid flow simulation. Lately, it is possible to see some efforts to enhance the full comprehension of the whole field and to develop a more robust well design by using 3D characterization techniques. This paper shows the steps involved in the development of a 3D geological-geomechanical model and how these models can be used as a robust tool to support decision makers. The methodology consists of preparing a geological model which comprises both overburden and reservoir zones, studying and distributing representative geomechanical facies, distributing properties/data of interest, applying correlations between initial data and rock mechanics properties, and calculating in situ stresses. Results of a case study show that an integrated analysis between geologists and geomechanical engineers is instrumental for an efficient 3D geomechanical characterization. Some direct benefits of these models are a global view of field behavior and integrated data, facilitating communication between expert teams, anticipating and preparing for possible drilling hazards and instantly extracting data for each desired well path, and increasing the reliability of well design.

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