A Quantitative Techno-Economic Assessment Model for Mountain Shale Gas Development Driven by Multi-Source Geospatial Data

The efficient development of shale gas in mountainous regions is critical for supporting China's energy security and transition towards carbon neutrality. However, the economic viability of such projects is heavily constrained by complex surface conditions, which introduce significant cost uncertainties that are difficult to quantify using conventional assessment methods. To address this, we develop a quantitative techno-economic model for mountain shale gas that integrates multi-source geospatial data. Framed within a real options analysis, the model expands the standard net present value calculation by incorporating not only traditional costs (e.g., fixed operations, exploration, royalties, surface engineering) but also spatially-variable costs derived from geospatial analysis. These include hazard mitigation, water access, ecological restoration, and community compensation.

Key spatial parameters are derived from open-access data, including high-resolution DEMs, multispectral imagery, land cover maps, infrastructure networks, and geohazard products. These datasets inform a comprehensive surface suitability assessment based on terrain ruggedness, slope, vegetation indices, and proximity to infrastructure, enabling the identification of viable wellpad locations and the estimation of maximum drillable wells. This process quantitatively translates spatial constraints into economic inputs. Monte Carlo simulation is then employed to analyze the sensitivity of project economics to key variables, particularly the number of wells and natural gas price volatility.

An application in the mountainous region of Western Hubei demonstrates the model's effectiveness in differentiating the economic potential of various blocks. The results quantify the substantial negative impact of surface complexity on both net present value and real option value, confirming well count and commodity price as the primary drivers of financial risk. This study presents a novel decision-support tool that systematically embeds geospatial data into the economic evaluation of shale gas resources in complex terrain. The developed "geospatial-data-to-economic-parameter" framework provides a transferable methodology for the techno-economic assessment of natural resource projects subject to strong spatial constraints.