Western Australia’s geological record contains multiple swarms of mafic dykes that significantly influence hydrogeological compartmentalisation within potential dewatering footprints of mining operations. These dykes can impact groundwater flow and mine water management. Accurate characterisation is therefore critical for hydrogeological modelling and mine planning. However, dyke identification is challenging. Their sub-horizontal, tabular geometry complicates drill hole interception, while extensive regolith and detrital cover limit conventional mapping. Weathering further obscures lithological features in drill core, reducing the reliability of visual logging. These constraints highlight the need for alternative approaches that utilise existing data sets without incurring additional costs. This study presents a litho-geochemical method that leverages immobile and semi-immobile elements commonly included in standard and historical assay suites, avoiding reliance on specialised or expensive analyses. Immobile elements are less affected by alteration and weathering, making them reliable indicators of igneous lithologies. A ranking system was developed to classify elements by mobility, enabling dolerite identification through immobile or less-mobile elements. Specifically, the TiO2/Cr ratio combined with vanadium (V) content forms the basis of a discriminant plot that separates dolerite from other lithologies in the Pilbara Province such as banded iron formation (BIF), shale, dolomite, and igneous rocks of the Fortescue and Weeli Wolli formations. The generation of the discriminant plot employed a bootstrap approach using interpreted stratigraphy as a guiding framework. However, samples plotting within the ‘geochemical dolerite’ field on the V versus TiO2/Cr diagram were identified as dolerites, independent of logging. Spatial correlation between these geochemically classified samples and modelled dyke intrusions shows strong alignment with geological and geophysical interpretations, confirming the robustness of the method. This approach offers two key advantages: cost-effectiveness, by extracting additional value from existing data sets, and resilience to weathering, mitigating the impact of mineralogical changes on lithological identification. The results provide a validation tool for lithological logging alongside traditional mapping, structural interpretation, and geophysical modelling. Ultimately, this method improves understanding of dyke distribution and continuity, supporting hydrogeological modelling and mine planning.