The objective of this study is to determine the minimal well length required to achieve a desired productivity index (PI). It considers the main uncertainties associated to fluids and reservoir properties (vertical and horizontal permeability, net oil thickness and oil viscosity). Monte Carlo analysis is used to consider possible combinations of these parameters and generate probabilistic results. This study was developed for a heavy oil reservoir. Oil of 15ºAPI or less and viscosities up to 150 cp are expected. The results obtained can be used in the planning phase. The reservoir properties are evaluated initially by a pilot well; afterwards they are estimated along the horizontal length. During the horizontal well drilling, this model can be easily updated. A theoretical model presented in JOSHI (1988) is used to calculate the horizontal well PI. It considers the influence of anisotropy in permeability. This work is divided in two parts. Initially, a sensibility analysis is performed regarding each uncertainty parameter separately. This first stage is necessary to evaluate the most impacting parameters. The procedure was applied for several well lengths. In a second phase, Monte Carlo analysis is applied, considering simultaneously the uncertainties associated to these parameters. This analysis provided three levels for well PI: pessimistic, most probable and optimistic curves as a function of well length. This methodology is flexible and, for this practical case, it was implemented through a spreadsheet that comprised the required probability density functions and the Monte Carlo analysis. It can be implemented with other development programs that suit the reservoir engineer. The results obtained can improve the estimates for the performance of the wells and can be used to design adequate horizontal wells for field development. Introduction This paper presents the key aspects of the study of determining the minimal well length in order to provide a desired productivity index (PI) as well as the strategy adopted in order to overcome the main reservoir uncertainties. There are several uncertainties involved in the prediction of a well productivity index. These uncertainties are present in rock properties, like net oil thickness and absolute permeabilities, in fluid properties, like viscosity, and properties depending on both, like relative permeabilities. In a horizontal well, vertical permeability is also an important factor to estimate the productivity. In order to model the reservoir behavior, a good estimate of well PI is necessary. Depending on its value, the initial oil rate can be considerably different. This effect is more important when the PI values are low, and it is the case of heavy oil fields. For this case, due to the challenging field environment - low API and viscous oil, and reservoir thickness ranging from 15 to 35 meters - the use of emerging technologies such as long horizontal wells and thermal insulated flow lines is required. The field is located at water depths ranging from 800 m to 2000 m, with small sediment cover of only 500 m in the studied area. The reservoir is Miocene sandstone with high porosity and permeability. The fluid distribution in the reservoir is quite complex. The field development comprises 17 production and 15 injection horizontal wells and the oil production is around 27.000 m3/d (170.000 bpd), with 14 production wells operating. Methodology In a horizontal well, several aspects must be considered to calculate the productivity. A methodology was presented by JOSHI (1988), considering several aspects involved in the problem, like well eccentricity and anisotropy influence in permeability. In the present study, skin factor and horizontal well eccentricity were not considered. Although there are several methods for predicting horizontal well productivity index (GIGER, 1983, KARCHER et al., 1986 etc.), JOSHI equation was adopted since its results represent better the values found in other wells in the same field.