Water Intrusion Characterization in Naturally Fractured Gas Reservoir Based on Spatial DFN Connectivity Analysis

In this study, the non-intrusive embedded discrete fracture model (EDFM) in combination with the Oda method are employed to characterize natural fracture networks fast and accurately, by identifying the dominant water flow paths through spatial connectivity analysis. The purpose of this study is to present a successful field case application in which a novel workflow integrates field data, discrete fracture network (DFN), and production analysis with spatial fracture connectivity analysis to characterize dominant flow paths for water intrusion in a field-scale numerical simulation. Initially, the water intrusion of single-well sector models was history matched. Then, resulting parameters of the single-well models were incorporated into the full field model, and the pressure and water breakthrough of all the producing wells were matched. Finally, forecast results were evaluated. Consequently, one of the findings is that wellbore connectivity to the fracture network has a considerable effect on characterizing the water intrusion in fractured gas reservoirs. Additionally, dominant water flow paths within the fracture network, easily modeled by EDFM as effective fracture zones, aid in understanding and predicting the water intrusion phenomena. Therefore, fracture clustering as shortest paths from the water contacts to the wellbore endorses the results of the numerical simulation. Finally, matching the breakthrough time depends on merging responses from multiple dominant water flow paths within the distributions of the fracture network. The conclusions of this investigation are crucial to field modeling and the decision-making process of well operation by anticipating water intrusion behavior through probable flow paths within the fracture networks.

Permeability Prediction of Iron Tailings Including Degree of Compaction and Structure

The stability of iron tailings dam is affected by the permeability of tailings. Considering the influence of it, it is necessary to analyze the permeability of tailings so as to prevent the recurrence of Brazilian iron tailings dam accidents. Nevertheless, the results of iron tailings permeability from some prediction equations (Terzaghi equation, Hazen equation, and Kozeny equation) cannot be accurate. Iron tailings are various as they can be divided into three categories: (1) silt content is less than 40%; (2) silt content is more than 40%, while clay content is less than 15%; and (3) clay content is more than 15% and less than 30%. Correspondingly, three equations are proposed to calculate the disturbed and iron undisturbed tailings permeability for the three types. And more accurate results come from it. The water-flow paths of the iron tailings are blocked after compaction, and the critical pressure of iron tailings blockage is 200 kPa. Although the porosity is large, some of the pores are isolated from each other when the pressure is larger than 200 kPa. However, porosity becomes too large for permeability calculation after compaction and the calculated permeability gets larger as well (equations (24)–(26)). Correcting the permeability calculation equations is an absolute must. The calculated permeability by the revised equations becomes more accurate (equations (27)–(29)). In fact, the granulometric characteristics necessarily play a vital role in the evolution of the pore interconnections by blocking the water-flow paths and modifying the morphological parameters. More research studies are required to be done in the future.

Analysis of the Ecological Effects of Decadal Large Scale Intermittent Annual Water Allocation using Satellite Data in Baiyangdian Wetland, Northern China

In this study, the ecological effects of intermittent water allocation with emphasis on spatiotemporal responses of the corresponding vegetation were analyzed using remote sensing data and GIS-based buffer technology considering the period from 1st July 2000 to 31st December 2009. Three sampling sites (Angzh, Wangk, and Xidayang) with different water flow paths and three buffer distances were distinguished in the research. The Seasonal-Trend decomposition procedure based on Regression (STR) trend extraction and its corresponding linear regression and anomaly detection were executed to determine temporal variations of vegetation under the effects of water allocation. ANOVA and PCA methods were employed to identify the spatial responses of vegetation to different water flow paths and buffer distances. The results were as follows: (1) NDVI except NDVImin displayed higher values during the period without water allocation; (2) extremely significant decline trends (p<0.001) of all NDVI categories were observed in all sites at all buffer distance levels, except for NDVImin at buffer distances of 2 km and 4 km in Angzh, showing stronger fluctuations of frequency after 2008 as well as the decline gradient with the extent of buffer distance to river. The anomaly detection results provided similar evidence of stronger NDVI fluctuations after 2008; (3) water allocation had extremely significant effects on regional vegetation coverage (p<0.01) with a decline gradient of statistical p values along enlarged buffer distances. Our results provide evidence of spatial and temporal differences in vegetation response to water availability due to the intermittent frequency water allocation implemented via different river channels. The findings of this study will deepen our understanding of the effects of water division on regional vegetation restoration and can be used to develop a practical strategy for effective implementation of water allocation.