Integration Adds Value to Deepwater Oil Exploration and Development: A Case Study of North Gulf of Mexico From Seismic and Well Log to Simulation

Abstract

Oil companies acquire all types of data, including well data and seismic data, for oil exploration and development. In order to maximize the value of the data in addressing the most important of reservoir and field-wide challenges, integration of various data and interpretation is a must.

This paper presents a case study of an oil field in the deepwater Gulf of Mexico where all the available data and results, including seismic data, high resolution resistivity borehole images, triaxial induction log, NMR, downhole fluid data, and core data, were carefully and methodically integrated to characterize the reservoir sands. Hemipelagic shale and slumped shale have similar bulk mineralogical compositions and petrophysical properties, they were distinguished based on textures from the borehole images and heterogeneity analyses from triaxial induction logs. Based on dips from borehole images, paleo flow directions of reservoir sands were defined. A relationship between lithofacies and a relative acoustic impedance (RAI) volume was established; and the lithofacies defined from wellbore data were populated into the 3D space guided by the RAI volume. The integrated study suggests the main reservoir of the field is a system of submarine lobe sands deposited above allochthonous salt in a mini basin. The lobe system concept was used in reservoir simulation. Both seismic isopach image analysis and DFA analysis indicate good lateral connectivity with limited vertical connectivity across the shale break. An erosional surface is posited as a possible shale pinchout establishing connectivity between upper and lower sands.

The corresponding geologic model with populated facies and properties (porosity, permeability and water saturation) provided a basis for a reservoir simulation model to demonstrate hydrocarbon-in-place and reservoir connectivity. A geobody extracted from seismic acoustic impedance (AI) helped to understand the reservoir performance. The model was validated by 1.5 years production and pressure data. The case study presented illustrates the role of coherent integration of diverse data to build robust models for history matching and simulation to guide field management and development decisions.

AAPG Datapages/Search and Discovery Article #90350 © 2019 AAPG Annual Convention and Exhibition, San Antonio, Texas, May 19-22, 2019