Solid Earth geoscience, geology, geochemistry, and geophysics, is increasingly served by large language models (LLMs) and multimodal LLMs (MLLMs) that combine text, geological maps, hyperspectral imagery, 3D structural models, spatial databases, and quantitative measurements into operational decision pipelines. Existing studies are fragmented across tasks, datasets, and system designs. This survey provides a structured review of LLM/MLLM research in solid-Earth geoscience along three axes: applications, modalities, and Memory-Reason-Act techniques. We identify five clusters of application (information extraction, knowledge Q A and retrieval, multimodal map and 3D interpretation, spatial predictive modelling, and agentic pipelines), characterise four modalities (text, visual, spatial, and quantitative signal) and their encoding gaps, and analyse Memory, Reasoning, and Action design choices with their failure modes. We further examine data resources and bias, and identify the absence of closed-loop drill-outcome validation as the central methodological gap blocking next-generation solid-Earth foundation models.

Mineral exploration requires integrating heterogeneous geochemical, geophysical, and geological evidence, yet existing prospectivity systems often provide only opaque scores or heatmaps. We present MineTRACE, a web-based system for evidence-grounded exploration of eight commodities: Cu, Au, Ni, W, Sn, Co, Ta, and Mn. Users can explore prospectivity maps, query locations or regions, inspect supporting evidence, and interact through natural language. A transparent expert tree, informed by geological knowledge and known deposits, combines multi-source evidence into interpretable prospectivity scores. For a new location, the conversational assistant retrieves the score and supporting evidence from the analysis pipeline and presents them in natural language. The scorer achieves spatial AUC values of up to 0.917 across different test scenarios, while end-to-end evaluation assesses query accuracy and response grounding. MineTRACE makes public geoscience data easier to access, interpret, and verify, supporting more efficient and transparent mineral exploration. Our video is available via https://geo.nlp-tlp.org/video, live demo is available via https://geo.nlp-tlp.org.