Next-Generation Workflow for Multi-level Assisted History Matching: Visualization and Collaboration
Authors: Carvajal G. A. , Maucec M. , Singh A. , Mahajan A. , Dhar J. , Villamizar M. , Mirzadeh S. , Knabe S. , Md-Adnan F. Md , Al-Jasmi A. K. , Nasr H. , Goel H.  K. 
Published: May 2016

Abstract
This paper outlines the visualization and collaboration attributes of an automated workflow that integrates the computer-assisted history matching (AHM), quantification of inherent model uncertainty, and optimization on production-forecast decisions. The workflow belongs to the group of smart flows for integrated asset management installed at the North Kuwait Integrated Digital Field (KwIDF) collaboration center.
The workflow is facilitated through four interactive user interfaces:Dashboard: displays history-match indices for water cut and visualizes maps of permeability, porosity, water and oil saturation, reservoir quality index, and reservoir pressure.Field and Well History Matching: displays well-level history matching and forecasting results filtered by water cut, bottomhole pressure (BHP), and liquid rate and visualizes the distributions of corresponding errors per simulated scenario.Dynamic Ranking: categorizes and ranks trends of forecasted oil recovery for history-matched models using multidimensional scaling and clustering techniques and visualizes identified P10, P50, and P90 models.Property Comparison: displays permeability maps for prior and history-matched models to identify the regions of improvement in terms of reservoir heterogeneity. Additionally, streamline trajectories colored by the time-of-flight provide excellent visualization of reservoir connectivity.
The workflow was applied in the pilot area of a major Middle East carbonate reservoir in North Kuwait and performs complex history matching and production forecasting. The simulation model combines 49 wells in 5 waterflood patterns to match 50 years of oil production, 12 years of water injection, and 8 years of forecasting.
The differentiator of this workflow is that it is unique in direct interfacing between the geomodeling application and reservoir simulator and in updating of high-resolution models with no upscaling. It delivers an optimized reservoir model for waterflood management and automatically updates the model quarterly with production, completion, and geological information. This allows engineers to improve the reservoir characterization and identify the areas that require more data capture.

Introduction
With the vision to transform the Kuwait Oil Company (KOC) through the application of integrated digital oilfield (iDOF) concepts and drive future KOC operations to the next level of excellence, the operator's senior management endorsed the development of a family of advanced integrated asset management (IAM) workflows, referred to as "smart flows," to optimize and integrate the subsurface models of the major Sabriyah-Mauddud (SaMa) reservoir with well models and network surface systems in various time horizons. The objective is to increase the effectiveness through automating work processes and shortening observation-to-action cycle time. The group of nine first-generation production engineering workflows focuses on production and operational activities and was launched at the KwIDF collaboration center in 2012. The workflows are introduced in Al-Abbasi et al. (2013) and described in greater detail in Al-Jasmi et al. (2013a) and references therein.