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Title: Local waterflooding assessment using 4D seismic data and reservoir simulation
Author: Obiwulu, Nkechi Nneka
ISNI:       0000 0004 8511 0072
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2018
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The substitution of oil with water that occurs during waterflooding triggers main 4D seismic effects of increased water saturation and increased pressure. In reservoir management and surveillance, increased waterflooding effects are typically interpreted for waterflood performance assessment using multiple data (geology, well logs, seismic data, production daya), reservoir simulation and seismic forward modelling technologies. This thesis focuses on the finer details of local or well-centric 4D seismic interpretation of waterflooding using integrated reservoir management. The main objective is to apply detailed interpretation of the local waterflooding 4D seismic signal to reservoir surveillance and management, through a reservoir engineering perspective. This facilitates evaluation of waterflooding performance, reservoir characterisation and reservoir model update. In this study, the influences of reservoir model scale on the synthetic seismic modelling, as well as significance of incorporating the individual waterflooding effects like salinity or temperature changes are estimated for a waterflooding scenario in a North Sea reservoir. The feasibility of resolving these influences given practical modelling conditions and approximations in reservoir engineering along with real seismic data are investigated to measure the resultant errors on the 4D seismic interpretation. Individual waterflooding effects are confirmed to impact the interpreted seismic signal. The magnitude of the added value of including this impact in 4D seismic signal interpretation is however seen to be data dependent. The relationship between 4D seismic signal and increased water saturation from waterflooding is established and used to calibrate net injected water volumes estimated from threedimensional geobodies of the 4D seismic water saturation signal to real production volumes. An extension of this relationship is the basis on which quantitative waterflooding seismic performance metrics are defined. The performance metrics are applicable to well-centric flood patterns for fast evaluation of oil displacement efficiencies and flood directionality. Combined resultant waterflood characterisation from the performance metrics gave good indications of field-scale sweep efficiencies, inter-well connectivity and possible waterflooding induced fractures. These interpretations of the 4D seismic flood patterns were then applied in reservoir model update via a local seismic automatic history matching using binary images and an evolutionary algorithm. Realisations from the geostatistical simulation of reservoir net-to-gross ratios constrained by seismic and well logs were used in a local automatic seismic history matching workflow. Binary image interpretations of the 4D seismic data were utilised in the optimisation of misfit reduction between observed 4D seismic and the simulated flood patterns. A new method of handling the mapped waterflood responses of saturation and pressure in spite of known uncertainties (of the contrasting seismic signal) led to improvements in the flood pattern match and the history matching result. Limitations of reduced heterogeneity in utilising binary images and obscuration of the water saturation signal by contrasting 4D seismic pressure response were evident in the history matching. The management of these highlighted the dependence of a successful seismic history matching exercise on a suitable dataset with clear depictions of waterflooding signals of saturation and pressure. The overall study emphasises the importance of early waterflood evaluation in waterflood surveillance for reservoir characterisation, prompt mitigation of waterflooding challenges and timely reservoir management decision making.
Supervisor: MacBeth, Colin ; Chassagne, Romain Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available