An Advanced Integrated Workflow for Estimation of Initial Zonal Productivity by Leveraging Openhole Logs and Formation Testing Data
Authors: Ghosal D. , Haddad S. , Solohaga D. E. , Abdulmoniem M. , Ahmed R. 
Published: February 2025

Abstract
The primary objective of this paper is to introduce an innovative, integrated workflow designed to quantify the expected initial productivity of oil and gas wells. This is achieved through the meticulous analysis of openhole logs and wireline formation testing data. The workflow is particularly beneficial for reservoir engineers and key decision-makers, offering them critical dynamic insights that are instrumental in shaping the future development strategies for different zones within a reservoir, thereby facilitating effective wellbore and reservoir management practices.
This workflow is a multi-disciplinary endeavour, incorporating data from geological, petrophysical, and reservoir engineering domains. The first pivotal step involves the creations of a discretized geological model, constructed using a plugin within an industry standard simulation software. Basic logs such as triple-combo and resistivity are employed after LQC to make the foundational structure of the static reservoir model; these logs assist in identification of significant lithological boundaries and distribution of reservoir properties across grid cells. Advanced datasets like Nuclear Magnetic Resonance (NMR), routine core analysis, formation pressure and mobility data from the wireline Formation Tester (FT) tool(s), etc. are utilized to capture finer-scale heterogeneities with superior resolution. A comprehensive depth-wise characterization of all zones is then formulated, to ascertain the representative permeabilities for each zone. Fluid models from PVT data of the field are assigned to different zones according to expected fluid types from FT fluids data and offset well data analysis. Once all data is imported into the simulation software, a Neural Network analysis is employed within the platform to segment the formations into distinct hydraulic flow units, using calibrated permeability, effective porosity, and saturation data. To further refine the model, Special Core Analysis (SCAL) data is integrated and assigned to the identified flow units, ensuring an accurate representation of reservoir behaviour.
The implementation of this fit-for-purpose workflow results in the construction of a robust 3D simulation model. The model is instrumental in making estimates concerning the initial zonal productivities. These simulation results were further corroborated through an independent multilayer network model developed using similar input parameters. This integrated suite of outputs not only offers invaluable insights that can aid choosing of optimal completion strategies, such as commingling or single selective completion, but also provides a platform for conducting sensitivity analyses. These analyses assess the potential impact of up to 10 uncertain production parameters, including water contacts and permeability anisotropy.
In conclusion, this research serves as a benchmark in innovation: it successfully develops a tailored workflow capable of predicting the dynamic attributes of different zones in a reservoir using only a single well's static data. This is the first time such an integrated end-to-end workflow has been created, relying on a borehole centric approach that helps customers take critical decisions from the minimum amount of data that is available.