Challenges and Opportunities of Modelling Long Horizontal Wells. A Case History

Abstract

Nikaitchuq is an oil field on the North Slope of Alaska that has been developed with more than 60 extended-reach wells having 6,000-ft to 18,000-ft-long horizontal sections. The main reservoir interval in Nikaitchuq corresponds to a shelfal lobe composed of two main sand bodies, encased in structural depressions. The development scheme consists of waterflood line drive with horizontal producers and water injection wells located side by side. The majority of the development wells were designed with a single horizontal trajectory undulating between the two main sands bodies in counter phase with the related water injectors. To be successful, such challenging well design requires accurate geological modeling, effective geosteering capabilities, and sensible well data acquisition. The objective of the approach here described is to correctly reconstruct the reservoir geometry by integrating numerous data and information coming from such long horizontal wells. However, data and information that have originated from different sources have different levels of accuracy. A thorough data quality assessment is a mandatory step in any data integration exercise. Hence, all information available in each horizontalwell section was reviewed in detail and cross-examined. Bed boundary mapping data interpretation via different inversion processes and log and image interpretations (such as gamma ray, neutron density, resistivity, density images, deep azimuthal electromagnetic data) were compared, validated, and integrated in the 3D geological model to perform a very precise reconstruction of reservoir internal geometry. Such accuracy in modeling was not only aimed at enhancing the precision of volumes in place and resource estimates, but it was also a prerequisite for the successful drilling of the subsequent wells during the field development. The novelty of the approach consisted in the integration of density image logs, bed boundary mapping data, and resistivity modeling results to derive accurate information on the reservoir geometry at a scale useful for 3D modeling. This use of data goes beyond common practices.