Proposing a New Approach for Horizontal Well Placement Optimization for Enhancing Oil Production

Optimizing the placement of wells is a crucial step in field development as it directly impacts production and cost. Inappropriate well placement can lead to decreased production and higher costs due to the expensive drilling process. Vertical well placement focuses on optimizing wellhead coordinates (x and y parameters), while horizontal and deviated wells require considering the depth of the wells (z parameter) along with operational limitations. This research presents an automatic framework that utilizes the particle swarm optimization algorithm to optimize the location of horizontal wells, taking into account drilling limitations. The objective function used is the net present value (NPV). This framework defines the number of particle swarm optimization variables based on operational constraints and well geometry. The algorithm randomly selects parameter values and applies the optimization procedure while considering specific constraints until the stop criteria are met. The framework successfully optimized the x, y, z, LP (Landing point), and KOP (Kick of Point) parameters in two heterogeneous synthetic models and a benchmark model (PUNQ_S3). On average, the net present value increased by 22% in all models, with greater heterogeneity resulting in a higher increase compared to homogeneous models.