Simulation history matching is a daunting, time-consuming task with numerous unknowns and several plausible answers. Scale differences in the data frequently obscure results, limiting its application in completion strategies. Good history matching does not guarantee accurate production forecasts, however. Reliable predictions, required for well planning, depend on the ability of the user to reduce the uncertainties to find consistent and timely solutions. Logs can provide appropriate conditioning data for history matching to enable its use for reservoir management.Electrofacies, capillary pressure, and absolute and relative permeability, imprinted on logs, can be mathematically linked with irreducible water saturation (S wi ). Unlike reservoir simulators, well logs are at the right scale for completion designs. Logs facilitate upscaling, honoring rock and fluid properties and the physics of flow (Haro 2006). Logs are snapshot measurements that are amenable for conversion into dynamic forecasting tools by use of flow and pressure equations. This concept permits creation of synthetic production logs (SPLTs) over time, from which production decline can be calculated.This method consists of integrating material balance, flow/ pressure algorithms, fluid data, cores, and log data. Thus, the corresponding analytical expressions are required. In this approach, every well represents a finite, gridded tank, capable of producing a measurable volume of fluids, limited by its petrophysical constraints. Superposition, in terms of pressure and flow, combines the various components within and among wells. The quality of the results is ensured because material balance must be honored at every depth at all times under different production scenarios and the prevailing drive mechanism.This log-handling technique helps when making strategic economic decisions to maximize reserves and optimize the reservoir-development plan. This strategy is used to obtain oil in place (OIP), drainage radii, lateral connectivity, fluid-bank arrival times, productivity indices (PIs), inflow performance relationship (IPR), production allocation, and recovery per zone per well. Current log analyses or simulators generally do not provide these parameters at this detail. This refined use of logs streamlines completion designs and improves conformance, enabling us to comply with an important part of daily reservoir management.