The Method and Practice of Constructing 3D Geological Model from Coalfield Exploration 2D Maps

3D geological modeling is an inevitable choice for coal exploration to adapt to the transformation of coal mining for green, fine, transparent and Intelligent mining. In the traditional Coalfield exploration geological reports, the spatial expression form for the coal seams and their surrounding rocks are 2D maps. These 2D maps are excellent data sources for constructing 3D geological models of coal field exploration areas. How to construct 3D models from these 2D maps has been studying in coal exploration industry for a long time, and still no breakthrough has been achieved so far. This paper discusses the principle, method and software design idea of constructing 3D geological model of an exploration area with 2D maps made by AutoCAD/MapGIS. At first, the paper analyzes 3D geological surface expression mode in 3D geological modeling software. It is pointed out that although contour method has unique advantages in coal field exploration, TIN (Triangular Irregular Network) is still the standard configuration of 3D modeling software for coal field. Then, the paper discusses the method of 2D line features obtaining elevation and upgrading 2D curve to 3D curve. Next, the method of semi-automatic partition is introduced to build the boundary ring of the surface patch, that is, the user clicks and selects the line feature to build the outer boundary ring of the surface patch. Then, Auto-process method for fault line inside of the outer boundary ring is discussed, it including construction of fault ring, determining fault ring being normal fault ring or reverse fault ring and an algorithm of dealing with normal fault ring. An algorithm of dealing with reverse fault ring is discussed detailly, the method of expanding reverse fault ring and dividing the duplicate area in reverse fault into two portions is introduced. The paper also discusses the method of extraction ridge line/valley line, the construction of fault plane, the construction of stratum and coal body. The above ideas and methods have been initially implemented in the “3D modeling platform for coal field exploration” software, and applied to the 3D modeling practice of data from several coal field exploration areas in Ningxia, Shanxi, Qinghai, etc.

Framework system and research flow of uncertainty in 3D geological structure models

Uncertainty in 3D geological structure models has become a bottleneck that restricts the development and application of 3D geological modeling.In order to solve this problem during periods of accuracy assessment,error detection and dynamic correction in 3D geological structure models,we have reviewed the current situation and development trends in 3D geological modeling.The main context of uncertainty in 3D geological structure models is discussed.Major research issues and a general framework system of uncertainty in 3D geological structure models are proposed.We have described in detail the integration of development practices of 3D geological modeling systems,as well as the implementation process for uncertainty evaluation in 3D geological structure models.This study has laid the basis to build theoretical and methodological systems for accuracy assessment and error correction in 3D geological models and can assist in improving 3D modeling techniques under complex geological conditions.

A 3D Geological Model Constrained by Gravity and Magnetic Inversion and its Exploration Implications for the World-class Zhuxi Tungsten Deposit, South China

The Zhuxi tungsten deposit in Jiangxi Province,South China,contains a total W reserve of about 2.86 Mt at an average grade of 0.54 wt%WO3,representing the largest W deposit in the world.Numerous studies on the metallogeny of the deposit have included its timing,the ore-controlling structures and sedimentary host rocks and their implications for mineral exploration.However,the deep nappe structural style of Taqian-Fuchun metallogenic belt that hosts the W deposit,and the spatial shape and scale of deeply concealed intrusions and their sedimentary host rocks are still poorly defined,which seriously restricts the discovery of new deposits at depth and in surrounding areas of the W deposit.Modern 3 D geological modeling is an important tool for the exploration of concealed orebodies,especially in brownfield environments.There are obvious density contrast and weak magnetic contrast in the ore-controlling strata and granite at the periphery of the deposit,which lays a physical foundation for solving the 3 D spatial problems of the ore-controlling geological body in the deep part of the study area through gravity and magnetic modeling.Gravity data(1:50000)and aeromagnetic data(1:50000)from the latest geophysical surveys of 2016-2018 have been used,firstly,to carry out a potential field separation to obtain residual anomalies for gravity and magnetic interactive inversion.Then,on the basis of the analysis of the relationship between physical properties and lithology,under the constraints of surface geology and borehole data,human-computer interactive gravity and magnetic inversion for 18 cross-sections were completed.Finally,the 3 D geological model of the Zhuxi tungsten deposit and its periphery have been established through these 18 sections,and the spatial shape of the intrusions and strata with a depth of 5 km underground were obtained,initially realizing―transparency‖for ore-controlling bodies.According the analysis of the geophysical,geochemical,and geological characteristics of the Zhuxi tungsten deposit,we discern three principles for prospecting and prediction in the research area,and propose five new exploration targets in its periphery.

Application of 3D Reservoir Geological Model on Es1 Formation, Block Nv32, Shenvsi Oilfield, China

Three-dimensional geological modeling of reservoirs is an essential tool to predict reservoir performance and improve the understanding of reservoir uniqueness in Es1 formation. The paper focuses on the use of petrel software to build three-dimensional reservoir geological model which characterizes and assesses block Nv32 that located in the west of the Shenvsi oilfield in the south of Cangzhou city, Hebei province of China, and has an oil-bearing area of 1.4 km2. This study is depending on integration data from well logs of 22 wells which provided from geology, geophysics, and petrophysics to identify and provide precise depict of the subsurface internal structure and the reservoir heterogeneity. Input data was used to build the structural model, sedimentary facies model, petrophysical properties (porosity, permeability, saturation, and N/G model, and finally to determine the reservoir volume. The lithological facies were simulated using the assigned value method. Moreover, Petrophysical properties (Porosity, permeability, oil saturation and net to gross) were constructed for each zone using the Sequential Gaussian Simulation method to guide the distribution of petrophysical properties of Es1 formation, block Nv32. Statistical analysis of the porosity, permeability, oil saturation and N/G model present that the porosity occurrence distribution is mainly concern between 0.2% - 36.39% of block Nv32 with an average porosity value of 17.5%, permeability between 0.017 mD to 974.8 mD, having an average permeability of 59.44 mD, oil saturation between 0.00 to 0.95 having an average value of 0.22, and N/G is mainly concentrated between 0.01 to 1.00 within an average value of 0.61. This research has indicated the reliability of the three-dimensional model technique as a suitable tool to provide a sufficient understanding of petrophysical distribution. The south-western and north-western indicate that oilfield is very promising an exploratory well should be drilled to find out the thickness and size of the reservoir.

Application of Sequential Indicator Simulation in Geological Study of X Oilfield in Zhujiangkou Basin

Sequential indicator simulation is a commonly used method for discrete variable simulation in 3D geological modeling and a widely used stochastic simulation method, which can be used not only for continuous variable simulation but also for discrete variable simulation. In this paper, the X Oilfield in the western South China Sea is taken as an example to compare the sequential indicator simulation method and the Indicator Kriging interpolation method. The results of the final comparison show that the results of the lithofacies model established by the Indicator Kriging deterministic interpolation method are overly smooth, and its coincidence rate with the geological statistical results is not high, thus cannot well reflect the heterogeneity of the underground reservoir, while the simulation results of the lithofacies model established by the sequential indicator stochastic simulation method can fit well with the statistical law of the well, which has eliminated the smoothing effect of Kriging interpolation, thus can better reflect the heterogeneity of the underground reservoir. Therefore, the sequential indicator simulation is more suitable for the characterization of sand bodies and the study of reservoir heterogeneity.

Coping with uncertainties through an automated workflow for 3D reservoir modelling of carbonate reservoirs

Reliable 3D modelling of underground hydrocarbon reservoirs is a challenging task due to the complexity of the underground geological formations and to the availability of different types of data that are typically affected by uncertainties. In the case of geologically complex depositional environments, such as fractured hydrocarbon reservoirs, the uncertainties involved in the modelling process demand accurate analysis and quantification in order to provide a reliable confidence range of volumetric estimations. In the present work, we used a 3D model of a fractured carbonate reservoir and populated it with different lithological and petrophysical properties. The available dataset also included a discrete fracture network(DFN) property that was used to model the fracture distribution. Uncertainties affecting lithological facies, their geometry and absolute positions(related to the fault system), fracture distribution and petrophysical properties were accounted for. We included all different types of uncertainties in an automated approach using tools available in today’s modelling software packages and combining all the uncertain input parameters in a series of statistically representative geological realizations. In particular, we defined a specific workflow for the definition of the absolute permeability according to an equivalent, single porosity approach, taking into account the contribution of both the matrix and the fracture system. The results of the analyses were transferred into a 3D numerical fluid-dynamic simulator to evaluate the propagation of the uncertainties associated to the input data down to the final results, and to assess the dynamic response of the reservoir following a selected development plan. The "integrated approach" presented in this paper can be useful for all technicians involved in the construction and validation of 3D numerical models of hydrocarbon-bearing reservoirs and can potentially become part of the educational training for young geoscientists and engineers, since an integrated and well-constructed workflow is the backbone of any reservoir study.

Modeling the Sediment Fill of the Upper Troy Pre-Glacial Bedrock Valley, McHenry County, Illinois, USA

The Troy Bedrock Valley (TBV) and its tributary valleys are the principal pre-glacial drainage in southern Wisconsin and northern Illinois, USA. This study focused on the headwaters of a tributary that occurs in McHenry County, IL. Drilling, geophysical surveys, and the analysis of existing geologic and water well data were used to determine the lithologic and geometric characteristics of the sediments that fill the paleovalley. A 3D geologic model of these sediments was then developed in Petrel. More than 65 m of Quaternary sediments filled the paleovalley. The model domain covers approximately 30 km2. The valley drains to the west and meanders, which is distinct from the straight course of the overlying modern Kishwaukee River. The sediments that filled the valley were subdivided into five units. These units include Illinois-age Glasford Formation coarse-grained proglacial outwash and alluvial deposits (GS2, GS1) and fine-grained lacustrine and diamicton deposits (G2 and G1). The Wisconsin-age Henry Formation sand and gravel cap the valley fill, and Cahokia alluvium buries everything.

Evaluation of urban underground space resources using a negative list method: Taking Xi'an City as an example in China

Utilization of urban underground space has become a vital approach to alleviate the strain on urban land resources,and to optimize the structure and pattem of the city.It is also very important to improve the city environment,build livable city and increase the capacity of the city.Based on the analysis of existing evaluation methods and their problems,a method for evaluating underground space resources based on a negative list of adverse factors affecting underground space development is proposed,to be primarily used in urban planning stages.A list of the adverse factors is established,including limiting factors,constraining factors and influencing factors.Taking Xi'an as an example,using a geographical information system platform,a negative list of adverse factors for the underground space resources in Xi'an City are evaluated,and preventive measures are proposed.Natural resources,exploitable resources,and the potential growth of exploitable underground space resources are evaluated.Underground space assessment in the different development stages of the city,collaborative utilization and safety evaluation for multiple subsurface resources,environmental impact and assessment,as well as evaluation methods based on big data and intelligent optimization algorithms are all discussed with the aim of serving city planning and construction.

Uncertainty Visualisation of a 3D Geological Geometry Model and Its Application in GIS-Based Mineral Resource Assessment:A Case Study in Huayuan District,Northwestern Hunan Province,China

This paper reports an application of uncertainty visualisation of a regional scale(1:50000)3 D geological geometry model to be involved in GIS-based 3 D mineral potential assessment of the Xiangxibei lead-zinc mineral concentration area in northwestern Hunan District,China.Three-dimensional(3 D)geological modelling is a process of interpretation that combines a set of input measurements in geometry.Today,technology has become a necessary part of GIS-based deep prospecting.However,issues of sparse data and imperfect understanding exist in the process so that there are several uncertainties in 3 D geological modelling.And these uncertainties are inevitably transmitted into the post-processing applications,such as model-based mineral resource assessment.Thus,in this paper,first,a big-data-based method was used to estimate the uncertainty of a 3 D geological model;second,a group of expectations of geological geometry uncertainty were calculated and integrated into ore-bearing stratoisohypse modelling,which is one of the major favourable parameters of assessment for Lead-Zinc(Pb-Zn)deep prospectivity mapping in northwestern Hunan;and finally,prospecting targets were improved.

Mineral Prospectivity Prediction via Convolutional Neural Networks Based on Geological Big Data

Today’s era of big data is witnessing a gradual increase in the amount of data,more correlations between data,as well as growth in their spatial dimension.Conventional linear statistical models applied to mineral prospectivity mapping(MPM)perform poorly because of the random and nonlinear nature of metallogenic processes.To overcome this performance degradation,deep learning models have been introduced in 3 D MPM.In this study,taking the Huayuan sedimentary Mn deposit in Hunan Province as an example,we construct a 3 D digital model of this deposit based on the prospectivity model of the study area.In this approach,3 D predictor layers are converted from the conceptual model and employed in a 3 D convolutional neural network(3 D CNN).The characteristics of the spatial distribution are extracted by the 3 D CNN.Subsequently,we divide the 22 extracted ore-controlling variables into six groups for contrast experiments based on various combinations and further apply the 3 D CNN model and weight of evidence(WofE)method on each group.The predictive model is trained on the basis of the coupling correlation between the spatial distributions of the variables and the underground occurrence space of the Mn orebodies,and the correlation between different ore-controlling factors.The analysis of 12 factors indicates that the 3 D CNN model performs well in the 3 D MPM,achieving a promising accuracy of up to 100%and a loss value below 0.001.A comparison shows that the 3 D CNN model outperforms the WofE model in terms of predictive evaluation indexes,namely the success rate and ore-controlling rate.In particular,the 1–12 ore-controlling factors selected in experiment 5 provide a significantly better prediction effect than the other factors.Consequently,we conclude that the Mn deposit in the study area is not only related to the stratum and interlaminar anomalous bodies but also to the spatial distribution of the faults.The experimental results confirm that the proposed 3 D CNN is promising for 3 D MPM as it eliminates the interference factors.