This paper presents the results of an investigation of the design and analysis of low conductivity fractures. The mathematical model used in this work is a practical alternative to estimate the degree of stimulation by means of a Stimulation Index (SD) and for evaluating the efficiency of wells with low conductivity hydraulically induced fractures. We utilize the dimensionless productivity index solution (JD) for finite-conductivity vertically fractured wells in closed rectangular bounded reservoirs and their corresponding pseudo-steady state shape factors under boundary-dominated flow conditions. Designing the optimum stimulation fracture treatment in this case is more heavily weighted on the achievable Stimulation Index (SD), for a given set of reservoir parameters and job sizes and on optimization of the flow rate and cumulative production.

We discuss the reasons for and alternatives to conductivity impairment within the fracture; fracture cleanup, width changes, conductivity degradation with time and stress effects are discussed. Field evidence indicates how these effects affect the fracture conductivity, affecting deliverability and inflow performance.

A practical performance criterion that focuses on conductivity improvement is used to improve performance of fractured wells. We use guidelines for choosing from the available fracture stimulation alternatives to focus on the technical merit of each technique and their application for improving fracture efficiency and deliverability, and include the use of higher breaker concentrations, lower polymer loads, and use of proppant with better resistance to stress (conductivity and permeability). Field examples and applications are provided for fracture stimulation evaluation and optimization.

This paper also introduces a way to evaluate and optimize the financial performance of fracture treatments. The financial criteria link the well deliverability or well potential (technical limits) to the fracture costs (or total well costs or OPEX).

Optimization is achieved by Net Present Value maximization and by generating an incremental return on investment due to the optimization steps. In this manner, we can financially quantify the engineered options for increasing well performance and optimization of the Stimulation Index (SD) while taking into account the associated costs into a financial model.

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