Summary Gas cap pressure maintenance while developing the associated oil rim is a critical aspect for optimum recovery. Preventing gas cap pressure dropping below dewpoint by injecting lean gas is essential for concurrent gas cap-oil rim development. Reservoir heterogeneity aggravates lean gas override causing preferential movement of lean gas plume. Thus, it is important to track lean gas plume while recycling and understanding the breakthrough potential of lean gas. This paper demonstrates a new workflow to track lean gas plume by estimating phase saturations with a case study from one of the giant oil and gas fields, Onshore, Abu Dhabi.
Pulsed neutron capture (PNC) tools are used for reservoir monitoring and surveillance. However, sigma log evaluation is insufficient to derive individual hydrocarbon phase saturations to monitor lean gas plume. Neutron response modeling (NRM) is devised to differentiate between lean and rich gas. NRM is a probabilistic solver with input of mineral and fluid phase parameters into tool response functions in petrophysical evaluation. To distinguish with discrete neutron fluid response between lean and rich gas, pressure/volume/temperature (PVT) data are utilized to derive hydrogen index, capture cross section, thermal decay length, and neutron macro parameters, such as neutron slowing down length and migration length. Neutron response is investigated for lean and rich gas with sensitivity of invasion effects on neutron log by calibrating to core porosity. The response for each phase under thermal neutron and capture modes with corresponding raw neutron log statistics is reviewed in both openhole and casedhole environments in known lean/rich gas intervals. Thirty-five wells spread across gas cap and oil leg with quality neutron log data are modeled and individual phase saturations are estimated.
The target reservoir is under development with over three decades of lean gas injection to support oil production. NRM results and phase saturations are validated with recent formation sampling, which enhanced the confidence in the overall workflow. Later, the results are verified to be in excellent agreement with lean gas injection and production history of the target reservoir. The identified movement of lean gas highlights nonuniform geology and gravity segregation of injected lean gas into upper members of the target reservoir. The results also emphasized the need for better injection support to lower members of the target reservoir where gas cap development is ongoing.
The solution presented is unique, particularly for lean gas injection projects by utilizing PVT for NRM based on neutron transport mechanism in pore fluids. Existing workflows require a special nuclear modeling platform with computationally expensive processing on data sets acquired using advanced logging technology. In spite of these prerequisites, existing workflows are not able to distinguish lean gas over rich gas. This paper effectively demonstrates NRM workflow distinguishing lean gas plume from rich gas using neutron logs and reveals compelling reservoir management insights. The sensitivity studies and practicality of this workflow highlight the fundamental importance of neutron logs in mature fields.