Mining-Induced Stress Control by Advanced Hydraulic Fracking under a Thick Hard Roof for Top Coal Caving Method: A Case Study in the Shendong Mining Area, China

Fully mechanized top-coal caving mining with high mining height, hard roofs and strong mining pressure are popular in the Shendong mining area, China. The occurrence of dynamic disasters, such as rock burst, coal and gas outburst, mine earthquakes and goaf hurricanes during the coal exploitation process under hard roof conditions, pose a threat to the safe production of mines. In this study, the characteristics of overburden fracture in fully mechanized top-coal caving with a hard roof and high mining height are studied, and the technology of advanced weakening by hard roof staged fracturing was proposed. The results show that the hard roof strata collapse in the form of large “cantilever beams”, and it is easy to release huge impact kinetic energy, forming impact disasters. After the implementation of advanced hydraulic fracturing, the periodic weighting length decreases by 32.16%, and the length of overhang is reasonably and effectively controlled. Ellipsoidal fracture networks in the mining direction of the vertical working face, horizontal fracture networks perpendicular to the direction of the working face, and near-linear fracture planes dominated by vertical fractures were observed, with the accumulated energy greatly reduced. The effectiveness of innovation technology is validated, and stress transfer, dissipation and dynamic roof disasters were effectively controlled.

Multi-phase Rate Transient Behaviors of the Multi-fractured Horizontal Well with Complex Fracture Networks

Complex fracture networks (CFN) provide flow channels and significantly affect well performance in unconventional reservoirs. However, traditional rate transient analysis (RTA) models barely consider the effect of CFN on production performance. The impact of multi-phase flow on rate transient behaviors is still unclear especially under CFN. Neglecting these effects could cause incorrect rate transient response and erroneous estimation of well and fracture parameters. This paper investigates multi-phase rate transient behaviors considering CFN, and tries to investigate in what situations the multi-phase models should be used to obtain more accurate results. Firstly, an embedded discrete fracture model (EDFM) is generated instead of LGR method to overcome time-intensive computation. The model is coupled with reservoir models using non-neighboring connections (NNCs). Secondly, eight cases are designed using the EDFM technology to analyze effect of natural fractures, formation permeability, and relative permeability on rate transient behaviors. Thirdly, Blasingame plot, log-log plot, and linear flow plot are used to analyze the differences of rate transient response between single-phase and multi-phase flow in reservoirs with CFN. For multi-phase flow, severe deviations can be observed on RTA plots compared with single-phase model. Combination of three RTA type curves can characterize the differences from early to late flow regimes and improve the interpretation accuracy as well as reduce the non-unicity. Finally, field data analysis in Permian Basin demonstrates that multi-phase RTA analysis are required for analyzing production and pressure data since single-phase RTA analysis will lead to big errors especially under high water cut during fracturing fluid flowback period, early production of unconventional gas wells or after waterflooding or water huff-n-puff.

Coupling Production Data with the DFN to Unravel Natural Fracture Networks in a Tight Naturally Fractured Jurassic Reservoir, Kuwait

The Jurassic Najmah-Sargelu of west Kuwait can be thought of as a "hybrid" between a conventional and an unconventional reservoir. These systems form an increasingly important resource for operators, but their performance is unpredictable because matrix permeability is in the micro-Darcy range and production depends on natural fractures. Success depends on how well the static models are aligned to the dynamic production, and the effectiveness of a fit-for-purpose multistage completion on project economics. In this work we present our lessons learnt in production modelling these reservoirs and the coupling between reservoir simulation and the discrete fracture network (DFN). Our reservoir models were constructed using a highly integrated approach incorporating data from all scales and disciplines (drilling, geophysical, geological, reservoir and production) and the production simulations were run using dual porosity and black oil models. As expected, the DFN played a key part of this effort. An iterative approach was used to adjust the DFN so that it was consistent with production observations. However, in all cases care was made to ensure the new DFN honoured the seismic, geological, well log and drilling data from which it was generated. Final, smaller adjustments were made to the simulation model at the log scale to match PLT data. We used uncertainty analysis to run hundreds of simulation cases and found that the character of the natural fractures is quite well imprinted in the observed production data, particularly pressure buildup data. This gave us a better understanding of whether the natural fractures are diffuse and laterally extensive away from the wellbore or if they are localized close to the wellbore. Where reservoir simulation history matches inferred laterally extensive natural fractures, an good correlation was obtained with the natural fracturing from the DFN. This correlation was poor where natural fracturing was confined to a smaller depth interval (as observed from PLT), and is a result of the limitation in seismic resolution to resolve these natural fractures. The lessons learnt from our work helps towards improved understanding of production mechanisms of these reservoirs and their natural fracture networks. This, together with higher resolution azimuthal seismic, advanced wellbore characterization data and multistage completions are the desired key ingredients for technically enhancing production in these reservoirs.

Impact of Complex Fracture Networks on Rate Transient Behavior of Wells in Unconventional Reservoirs Based on Embedded Discrete Fracture Model

It has recently been demonstrated that complex fracture networks (CFN) especially activated natural fractures (ANF) play an important role in unconventional reservoir development. However, traditional rate transient analysis (RTA) methods barely investigate the impact of CFN or ANF. Furthermore, the influence of CFN on flow regime is still ambiguous. Failure to consider these effects could lead to misdiagnosis of flow regimes and underestimation of original oil in place (OOIP). A novel numerical RTA method is therefore presented herein to improve the quality of reserves assessment. A new methodology is introduced. Propagating hydraulic fractures (HF) can generate different stress perturbations to allow natural fractures (NF) to fail, forming various ANF pattern. An embedded discrete fracture model (EDFM) of ANF is stochastically generated instead of local grid refinement (LGR) method to overcome the time-intensive computation time. These models are coupled with reservoir models using non-neighboring connections (NNCs). Results show that except for simplified models used in previous studies subjected to traditional concept of stimulated reservoir volume (SRV), in our study, the ANF region has been discussed to emphasis the impact of NF on simulation results. Henceforth, ANF could be only concentrated around the near-wellbore region, and it may also cover the whole simulation area. Obvious distinctions could be viewed for different kinds of ANF on diagnostic plots. Instead of SRV-dominated flow mentioned in previous studies, ANF-dominated flow developed in this work is shown to be more reasonable. Also, new flow regimes such as interference flow inside and outside activated natural fracture flow region (ANFR) are found. In summary, better evaluation of reservoir properties and reserves assessment such as OOIP are achieved based on our proposed model compared with conventional models. The novel RTA method considering CFN presented herein is an easy-to-apply numerical RTA technique that can be applied for reservoir and fracture characterization as well as OOIP assessment.

Fracture Network Localization Preceding Catastrophic Failure in Triaxial Compression Experiments on Rocks

We quantify the spatial distribution of fracture networks throughout six in situ X-ray tomography triaxial compression experiments on crystalline rocks at confining stresses of 5–35 MPa in order to quantify how fracture development controls the final macroscopic failure of the rock, a process analogous to those that control geohazards such as earthquakes and landslides. Tracking the proportion of the cumulative volume of fractures with volumes >90th percentile to the total fracture volume, ∑v90/vtot indicates that the fracture networks tend to increase in localization toward these largest fractures for up to 80% of the applied differential stress. The evolution of this metric also matches the evolution of the Gini coefficient, which measures the deviation of a population from uniformity. These results are consistent with observations of localizing low magnitude seismicity before large earthquakes in southern California. In both this analysis and the present work, phases of delocalization interrupt the general increase in localization preceding catastrophic failure, indicating that delocalization does not necessarily indicate a reduction of seismic hazard. However, the proportion of the maximum fracture volume to the total fracture volume does not increase monotonically. Experiments with higher confining stress tend to experience greater localization. To further quantify localization, we compare the geometry of the largest fractures, with volumes >90th percentile, to the best fit plane through these fractures immediately preceding failure. The r2 scores and the mean distance of the fractures to the plane indicate greater localization in monzonite than in granite. The smaller mean mineral diameter and lower confining stress in the granite experiments may contribute to this result. Tracking these various metrics of localization reveals a close association between macroscopic yielding and the acceleration of fracture network localization. Near yielding, ∑v90/vtot and the Gini coefficient increase while the mean distance to the final failure plane decreases. Macroscopic yielding thus occurs when the rate of fracture network localization increases.