Economic and geospatial drivers of conflict are established, yet aggregate analyses often obscure subnational risk patterns. This study develops a high-resolution risk methodology for fragile, resource-rich states by combining spatial econometrics with the greed-grievance framework. Using a Bayesian approach based on integrated nested Laplace approximation and stochastic partial differential equations, we examine how socio-economic development, natural resources, energy infrastructure, and 14 spatial variables shape four conflict typologies in Nigeria between 1997 and 2023. Results show that wealth reduces conflict risk, while ethnic fractionalization and proximity to resources have actor-specific effects. Petroleum endowments and power infrastructure increase organized rebel and militia activity, whereas ethnic dynamics mainly drive riots. Predictive risk maps support infrastructure planning, supply chain risk mitigation, and targeted stabilization policies.