A New Approach for Reservoir Connectivity Assessment and Flow Assurance Prediction Applying Reservoir Fluid Geodynamics

Autor: Endurance Ighodalo, Mustapha Berkane, Tariq Mattar, Mohammed Abdulmoniem
Rok vydání: 2023
Zdroj: Day 3 Fri, March 03, 2023.
Popis: Traditional approach relys on reservoir pressures to assess reservoir connectivity in low permeability formations. This paper will present a new approach of applying Reservoir Fluid Geodynamics (RFG) through Flory Huggins-Zuo (FHZ) equation of state (EOS) for asphaltene distributions to determine reservoir connectivity and fluid typing in undrilled locations. FHZ-EOS asphaltene gradient was constructed with data from downhole fluid samples in different wells covering two zones (A and B). The downhole fluid analysis (DFA) results were validated with laboratory analysis. The structural continuity of both zones across the study area in the field was validated using a wide range of geological data including conventional open-hole logs. The resulting FHZ-EOS model formed the basis for fluid typing, correlation and connectivity across layers. The DFA data was used in real time at different stages of formation fluid sampling cleanup to correlate the samples quality with the existing model. The DFA data used in real time in conjunction with the pre-built FHZ-EOS model, improved the sampling quality check process and confidence in the sample quality, especially in the presence of low gas oil ratio (GOR) fluids. This improvement in real time data quality helped to optimize the pumping time and reduce the number of samples in each reservoir since the confidence in the sample quality was high. The constructed asphaltene gradient from the FHZ-EOS model also confirm the hydrocarbon continuity both vertically and laterally in undrilled locations with the study area of the field. For each of the zones, the data analysis shows a clear and distinct asphaltene gradient with different asphaltene molecule sizes. This supports the presence of heavy oil / tar towards the deeper sections of the area of interest within the field. It also predicted the depths / location of the heavy oil / tar, which will assist in the field development plan and flow assurance.
Databáze: OpenAIRE