A framework for reinterpretation of legacy hydrocarbon data for sustainable groundwater mapping: Case studies from the Napuu and Lotikipi Aquifers, Kenya

Abstract

Groundwater resources are increasingly critical for climate resilience, particularly in arid and semi-arid regions. Yet groundwater mapping remains challenging due to sparse hydrogeological data. Meanwhile, oil and gas exploration has generated extensive subsurface datasets, including seismic and well log data, which remain underutilized for groundwater studies. This paper presents a general framework on how oil and gas subsurface data can be repurposed to identify sustainable shallow groundwater resources, addressing the gap caused by limited dedicated groundwater data. The framework, which is based on seismic and well logs, involves the assessment of stratigraphy, aquifer characteristics, water quality and chemistry, structural influences on groundwater distribution, and hydro-stratigraphic interpretation. This approach is applied to Kenya's Napuu and Lotikipi aquifers. Results reveal that in the Napuu Aquifer, the fluvial and coarse sandstones between 300–1000 m represent the most promising targets, with confirmed high permeability (20–80 m/day), porosity exceeding 20 % and fresh to slightly brackish water (TDS-Total Dissolved Solids) 600–1200 mg/L), supported by pressure testing. In the Lotikipi Aquifer, the Pliocene sandstone unit (LKT76), located between 220–470 m, emerged as the most promising aquifer zone. It displays high porosity (24–32 %), excellent permeability (20–80 m/day), and favorable water quality with TDS values between 500–1000 mg/L. Structural analysis highlighted major normal faults influencing aquifer compartmentalization and recharge pathways in both aquifers. Deeper formations beyond 1000 m displayed reduced permeability and higher salinity, reinforcing the focus on shallower groundwater development. These insights demonstrate how existing oil and gas data can significantly enhance groundwater exploration, supporting climate-resilient water management in data-scarce regions.