A method for creating a field development plan by a specially programmed computing system, including number, placement and type of wells within a hydrocarbon field, the method comprising: initializing a connectivity model based on field development data for predicting hydrocarbon production in a reservoir based on reservoir connectivity; characterized by calibrating the connectivity model by simulating one or more reservoir simulation cases where wells are randomly placed in the reservoir and subsequently tuning, using an internal optimization algorithm, one or more parameters associated with the connectivity model; determining a travel time between wells and reservoir cells using a fast marching method, wherein the travel time is based on a velocity between a first cell and a second cell, expressed using the equation t AB = ∑ i ∈ L AB d i v i where t AB is travel time from a first cell A to a second cell B, L AB represents a set of cells in the shortest path between cell A and cell B, v i represents the velocity between neighboring cells, and d i represents distance between the said neighboring cells; wherein velocity is based on Darcy's law v i = k μ ∇ p, where k represents the intrinsic permeability of the medium, μ represents the length of where the pressure drop is taking place and Vp represents the pressure gradient vector, and wherein the velocity is determined using either a linear pressure computation, or using an approximate two-dimensional pressure solver using steady-state pressure equations: ∇ ∗ k λ t ∇ p = 0 p x well = BHP; determining a hydrocarbon saturation based on the travel time to construct a model prediction, including generating a plurality of possible development plans with varying number of wells ad well locations; optimizing the connectivity model using a global optimization using a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, and/or a pattern search algorithm, and a local optimization using a random walk algorithm or a polytope optimization algorithm; verifying the optimized connectivity model; and constructing at least one well file using the optimized connectivity model. initializing a connectivity model based on field development data for predicting hydrocarbon production in a reservoir based on reservoir connectivity; characterized by calibrating the connectivity model by simulating one or more reservoir simulation cases where wells are randomly placed in the reservoir and subsequently tuning, using an internal optimization algorithm, one or more parameters associated with the connectivity model; determining a travel time between wells and reservoir cells using a fast marching method, wherein the travel time is based on a velocity between a first cell and a second cell, expressed using the equation t AB = ∑ i ∈ L AB d i v i where t AB is travel time from a first cell A to a second cell B, L AB represents a set of cells in the shortest path between cell A and cell B, v i represents the velocity between neighboring cells, and d i represents distance between the said neighboring cells; wherein velocity is based on Darcy's law v i = k μ ∇ p, where k represents the intrinsic permeability of the medium, μ represents the length of where the pressure drop is taking place and Vp represents the pressure gradient vector, and wherein the velocity is determined using either a linear pressure computation, or using an approximate two-dimensional pressure solver using steady-state pressure equations: ∇ ∗ k λ t ∇ p = 0 p x well = BHP; wherein the travel time is based on a velocity between a first cell and a second cell, expressed using the equation t AB = ∑ i ∈ L AB d i v i where t AB is travel time from a first cell A to a second cell B, L AB represents a set of cells in the shortest path between cell A and cell B, v i represents the velocity between neighboring cells, and d i represents distance between the said neighboring cells; wherein velocity is based on Darcy's law v i = k μ ∇ p, where k represents the intrinsic permeability of the medium, μ represents the length of where the pressure drop is taking place and Vp represents the pressure gradient vector, and wherein the velocity is determined using either a linear pressure computation, or using an approximate two-dimensional pressure solver using steady-state pressure equations: ∇ ∗ k λ t ∇ p = 0 p x well = BHP; determining a hydrocarbon saturation based on the travel time to construct a model prediction, including generating a plurality of possible development plans with varying number of wells ad well locations; optimizing the connectivity model using a global optimization using a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, and/or a pattern search algorithm, and a local optimization using a random walk algorithm or a polytope optimization algorithm; verifying the optimized connectivity model; and constructing at least one well file using the optimized connectivity model.