Alternative geostatistics tools applied to Morroa aquifer modeling (Sucre-Colombia)


  • Aníbal Pérez-García Universidad Antonio Nariño
  • Nelson Obregón-Neira Universidad Javeriana
  • Oscar García-Cabrejo Universidad Javeriana


Morroa Aquifer, groundwater modeling, geostatistics, conditional stochastic simulation, multiple-point statistics, soft data, hard data


In this paper, stochastic simulations and some multiple-point geostatistical principles are developed using a comparative methodology consisting of two phases. First, a traditional methodology based on variogram concepts called Conditional Stochastic Simulation (CSS) and more specifically the Sequential Indicator Simulation (SISIM) is applied to the aquifer modeling. Secondly, modern algorithm based on multiple-point geostatistics called SNESIM [1] and ζ Model [4] are implemented to integrate information available in the definition of Morroa aquifer facies. The simulations are realized by using algorithms constructed in references [1, 2] and S-Gems software prepared at Stanford University[3]. Results show the convenience of employing training images with soft and hard data conditioning integrated by ζ Model, and CSS for configuring hydrogeological models when barely deficient information is available.

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How to Cite

Pérez-García, A., Obregón-Neira, N., & García-Cabrejo, O. (2013). Alternative geostatistics tools applied to Morroa aquifer modeling (Sucre-Colombia). Revista Facultad De Ingeniería Universidad De Antioquia, (50), 63–76. Retrieved from