3-D Tunnel Seismic Advance Prediction Method with Wide Illumination and High-Precision

Tunnel seismic advance prediction can effectively reduce the construction risk during tunnel excavation.Compared with the 2-D method,the 3-D method is more conducive to describing the spatial characteristics of the geological body by adding the seismic data in the vertical direction.However,some drawbacks still need improvement in the current 3-D tunnel seismic prediction method.(1)The geometry is complex,which is destructiveness,high cost,and time-consuming,and will delay the tunnel construction schedule.(2)Illumination of the anomalous body is insufficient,and the precision of migration imaging is low.(3)Shot points are far away from the tunnel face,the energy loss at the shot points is more serious.(4)The received signals at the tunnel wall have the surface wave with strong energy when the shot points are placed on the tunnel wall.(5)The geometry is not linear,so the directional filtering method cannot be used to extract the reflection wave.To overcome the drawbacks of the current prediction method,a new 3-D symmetrical tunnel seismic prediction method is proposed.Six geophones are installed on the tunnel wall,two on the left side,two on the right side,and two on the top side.Twenty-four shot points are placed on the tunnel face and near both sides of the tunnel wall,twelve shot points on the left side and twelve shot points on the right side.The shot points will move along with the forward excavation of the tunnel.The wavefield analysis,illumination statistics,and 3-D reverse time migration imaging are used to evaluate the proposed method.The result of modeled data indicates that the proposed 3-D geometry has some advantages:(1)the geometry is simple and the geophone installation time is short;(2)it has high illumination energy,wide illumination range,and can improve the prediction distance and imaging accuracy;(3)the proposed 3-D method can better estimate the velocity of surrounding rock and is more conducive to extracting the reflection wave with high resolution.

Paleontology Knowledge Graph for Data-Driven Discovery

A knowledge graph(KG)is a knowledge base that integrates and represents data based on a graph-structured data model or topology.Geoscientists have made efforts to construct geosciencerelated KGs to overcome semantic heterogeneity and facilitate knowledge representation,data integration,and text analysis.However,there is currently no comprehensive paleontology KG or data-driven discovery based on it.In this study,we constructed a two-layer model to represent the ordinal hierarchical structure of the paleontology KG following a top-down construction process.An ontology containing 19365 concepts has been defined up to 2023.On this basis,we derived the synonymy list based on the paleontology KG and designed corresponding online functions in the OneStratigraphy database to showcase the use of the KG in paleontological research.