Well Productivity Index Degradation - Applied Modeling Workflow

Abstract

Productivity index (PI) reduction is a recognized phenomenon in oil and gas production to the extent that production becomes uneconomic. Productivity index (PI) decrease may be caused by several factors arising from reservoir, completion, and operational issues. The reservoir-related factors include compaction, fines migration, pressure support and multi-phase fluid flow. The completion-related issues arise from frac-pack geometry and stress-sensitivity of proppant conductivity. Finally, operational issues such as pressure drawdown at the sandface and induced flux (the movement of fluids across the completion) may also play a large role in PI degradation. Understanding the interactions of different parameters controlling the PI behavior and the resultant well performance is paramount for maximizing the ultimate recovery and net-present value or NPV. PI modeling may offer several challenges because it involves non-unique solutions for reservoirs and near-wellbore and well-completion status, in addition to manual data entry subject to human errors, uncertainties in reservoir parameters, and poor quality field data. This study presents a workflow for modeling well PI degradation for an over-pressured gas/condensate reservoir in deep offshore Gulf of Mexico. An automated procedure was tailored and applied to match production history by adjusting both the reservoir and well completion parameters. Among the reservoir parameters considered were horizontal stresses, rock compressibility, absolute permeability, relative-permeability endpoints and curvature, porosity, stress-sensitive permeability and porosity. The well completion parameters included fracture length, height, width, conductivity, and stress. A "Tabu Scatter Search" optimizer engine (April et al, 2003) selected the optimal values of a set of input parameters to minimize the objective function, i.e. the error between the measured and calculated PI values. Both reservoir and well completion parameters contributing to PI degradation were identified, and compared to those obtained by alternate methods. The relative and combined contributions of stress-sensitive reservoir compressibility, permeability, porosity, and fracture conductivity all helped understand well performance and guide decisions towards optimum well operating envelope.

Strategy for Optimum Chemical Enhanced Oil Recovery Field Operation

“…Furthermore, the cost of installation, maintenance, and repair of surveillance equipment should be considered in the overall project economics. For more details, please refer to Yznaga et al 2019and Saputelli et al 2010. Volokitin et al 2017 discussed the pilot surveillance program including estimation of chemical efficiency, evaluation of residual oil saturation (before and after the chemical injection), chemical retention, and dynamic reservoir model calibration.…”

Wavelet Frequency Analysis of Long-term Transient Pressure from Permanent Down-Hole Gauges (PDG) for the Real-Time Reservoir Monitoring

“…These changes in reservoir properties and well conditions can cause production problems. For instance, significant production index losses have been observed in deep offshore Gulf of Mexico reservoirs due to compaction near the wellbore, increasing skin, or relative permeability changes after water production (Saputelli et al 2010). Holicek et al (2008) presented another deep-water field case, where there were reduction in permeabilityheight and increasing skin due to formation damage.…”