The geochemistry of a coastal aquifer was assessed using statistical and geospatial analysis tools for the pre-monsoon, rainy and post-monsoon seasons. Data were obtained from both the field and laboratory analysis of water samples. Statistical methods such as correlation coefficients, piper plots, factor analysis and mixing index were used to gain insights into the geochemistry, while geospatial tools were used to create contours to understand the spatial distribution of the measured groundwater parameters of the coastal aquifer. The measured groundwater levels ranged from -0.84 to 30.08 m above mean sea level. The Electrical Conductivities and Total Dissolved Solids values were observed to have perfectly correlated with each other. Groundwater salinities were generally high, as over 94% of the water samples tested exceeded the WHO drinking water limit of 750 lS/cm and 500 mg/l, respectively. The groundwater pH was generally slightly alkaline but could be slightly acidic in the rainy season. The Na ? , K ? , Mg 2? , Cl -and SO 4 2-were observed to have high impacts on the geochemistry and also had tendencies to form similar trends. EC, TDS and NaCl values above 1000 mg/l in the groundwater were observed to generally skew towards the ocean during the rainy season. The principal process influencing the geochemistry was found to be seawater intrusion, while mineral dissolutions and rainwater percolation play lesser roles. The aquifer predominantly comprises Na-Cl waters of marine origin. The study shows the growing importance and applicability of integrated statistical and geospatial approaches for better understanding of groundwater and geochemistry of aquifers.

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Lamu Basin is located in South Eastern Kenya and covers about 170 000 km2 both onshore and offshore. Kenya’s Lamu Basin is hitherto underexplored even though there have been notable oil and gas discoveries along the margin of East Africa. This study focuses on the shallow section of the Lamu offshore bounded by 39°E to 43°E by 2°S to 6°S, whereby, unfortunately, some of the wildcat wells turned out to be dry although expensive. Gravity interpretation techniques such as spectral analysis and first horizontal derivative were applied to the reduced gravity data to delineate and model structures to minimize the high investment risks. The gravity data used in this study were sourced from the International Gravity Bureau (BGI) and National Oil Corporation of Kenya (NOCK) digital data courtesy of companies like Woodside Energy, Anadarko Kenya Limited, and Total Exploration and Production companies. The obtained reduced gravity data were gridded to produce the gravity anomaly grids (Free air, Bouguer, and Isostacy), which were consequently drawn into maps. From spectral analysis, depths to shallow sources and deep sources were estimated. These depths were used to set regional and residual separation filters using the Gaussian filter. The first horizontal derivative (FHD) applied to the regional Isostatic gravity anomaly map yielded features that were inferred as intrasediment fractures/faults trending in NW-SE and NE-SW directions. The features like the ridges, troughs, and faults mainly trending in the NW-SE direction are discernable from the regional anomaly map. The developed models show the basement highs and lows with a possibility of anticlinal and synclinal structures and thick sedimentary successions likely to represent good hydrocarbon source kitchens.

The ever-increasing demand for oil and gas has driven its exploration in rather extreme conditions. In Lamu offshore, which is hitherto underexplored, most of the wells already drilled turned out dry save for a few wells with hydrocarbon shows despite the promising reservoir properties and related geo-

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