This project is a research into the effect of gas condensate damage in hydraulically fractured wells. It is the result of a problem encountered in producing a low permeability formation from a well in South Texas owned by the El Paso Production Company. The well was producing from a gas condensate reservoir. Questions were raised about whether flowing bottomhole pressure below dewpoint would be appropriate. Condensate damage in the hydraulic fracture was expected to be of significant effect. In the most recent work done by Adedeji Ayoola Adeyeye, this subject was studied when the effects of reservoir depletion were minimized by introduction of an injector well with fluid composition the same as the original reservoir fluid. He also used an infinite conductivity hydraulic fracture along with a linear model as an adequate analogy. He concluded that the skin due to liquid build-up is not enough to prevent lower flowing bottomhole pressures from producing more gas. This current study investigated the condensate damage at the face of the hydraulic fracture in transient and boundary dominated periods when the effects of reservoir depletion are taken into account. As a first step, simulation of liquid flow into the fracture was performed using a 2D 1-phase simulator in order to help us to better understand the results of gas condensate simulation. Then during the research, gas condensate models with various gas compositions were simulated using a commercial simulator (CMG). The results of this research are a step forward in helping to improve the management of gas condensate reservoirs by understanding the mechanics of liquid build-up. It also provides methodology for quantifying the condensate damage that impairs linear flow of gas into the hydraulic fracture.

Neural networks (NNs) are widely used to investigate the relationship among variables in complex multivariate problems. In cases of limited data, the network behavior strongly depends on factors such as the choice of network activation function and network initial weights. In this study, I investigated the use of neural networks for multivariate analysis in the case of limited data. The analysis shows that special attention should be paid when building and using NNs in cases of limited data. The linear activation function at the output nodes outperforms the sigmoidal and Gaussian functions. I found that combining network predictions gives less biased predictions and allows for the assessment of the prediction variability. The NN results, along with conventional statistical analysis, were used to examine the effects of folding, bed thickness, structural position, and lithology on the fracture properties distributions in the Lisburne Formation, folded and exposed in the northeastern Brooks Range of Alaska. Fracture data from five folds, representing different degrees of folding, were analyzed. In addition, I modeled the fracture system using the discrete fracture network approach and investigated the effects of fracture properties on the flow conductance of the system. For the Lisburne data, two major fracture sets striking north/south and east/west were studied. Results of the NNs analysis suggest that fracture spacing in both sets is similar and weakly affected by folding and that stratigraphic position and lithology have a strong effect on fracture spacing. Folding, however, has a significant effect on fracture length. In open folds, fracture lengths in both sets have similar averages and variances. As the folds tighten, both the east/west and north/south fracture lengths increase by a factor of 2 or 3 and become more variable. In tight folds, fracture length in the north/south direction is significantly larger than in the east/west direction. The difference in length between the two fracture sets creates a strong anisotropy in the reservoir. Given the same fracture density in both sets, the set with the greater length plays an important role for fluid flow, not only for flow along its principal direction but also in the orthogonal direction.

Fractures make both opportunities and problems for exploration and production from hydrocarbon reservoirs. It is always difficult to predict how to optimally produce a fractured reservoir due to the complexity and heterogeneity of fluid flow paths. The following behavior is seen in fractured reservoirs: early water breakthroughs, reduced tertiary recovery efficiency due to channeling of injected gas or fluids, dynamic calculations of recoverable hydrocarbons that are much less than static mass balance and dramatic production changes due to changes in reservoir pressure as fractures close down as conduits. These problems often lead to reduced ultimate recoveries or higher production costs. Polymer gels, in particular in-situ gels that can be placed deep into the reservoir, have been widely used for improved conformance control. In this dissertation, we aim to block the high-permeability zones, fractures in particular, with the microgels to increase the sweep efficiency by diverting the waterflood water to the low permeability zones that still contain unswept oil. vii Polyacrylic acid microgels can swell a thousand fold as the pH of the surrounding solution changes, with an accompanying large increase in viscosity. This pH trigger is simpler than chemical cross-linking and thus offers operational advantages. The ability of pH-sensitive polymers to block high permeability fractures is studied by performing several coreflood and batch experiments. The effect of different rock and salt minerals, polymer concentration, polymer salinity, and temperature on polymer performance is studied in this dissertation. Polymer microgels show excellent consistency in the presence of various salt minerals and in contact with different rock minerals. The placement of microgels into the fractures lowered the overall core permeability in all cases. In addition, polymer microgels were stable after being in reservoir for a month with conditions at 58°C. Consequently, using pH-triggered polymers for conformance control and reducing the permeability of high permeability areas in fractured reservoirs merit further investigations. These polymers are inexpensive and are easy to prepare. The polymer concentration, salinity and shut-in time could be set according to the desired PRF value, injectivity, propagation distance and reservoir mineralogy. / text

Modeling and simulation of fluid flow in subsurface fractured systems has been steadily a popular topic in petroleum industry. The huge potential hydrocarbon reserve in naturally and hydraulically fractured reservoirs has been a major stimulant for developments in this field. Although several models have found limited applications in studying fractured reservoirs, still more comprehensive models are required to be applied for practical purposes. A recently developed Embedded Discrete Fracture Model (EDFM) incorporates the advantages of two of the well-known approaches, the dual continuum and the discrete fracture models, to investigate more complex fracture geometries. In EDFM, each fracture is embedded inside the matrix grid and is discretized by the cell boundaries. This approach introduces a robust methodology to represent the fracture planes explicitly in the computational domain. As part of this research, the EDFM was implemented in two of The University of Texas in-house reservoir simulators, UTCOMP and UTGEL. The modified reservoir simulators are capable of modeling and simulation of a broad range of reservoir engineering applications in naturally and hydraulically fractured reservoirs. To validate this work, comparisons were made against a fine-grid simulation and a semi-analytical solution. Also, the results were compared for more complicated fracture geometries with the results obtained from EDFM implementation in the GPAS reservoir simulator. In all the examples, good agreements were observed. To further illustrate the application and capabilities of UTCOMP- and UTGEL-EDFM, a few case studies were presented. First, a synthetic reservoir model with a network of fractures was considered to study the impact of well placement. It was shown that considering the configuration of background fracture networks can significantly improve the well placement design and also maximize the oil recovery. Then, the capillary imbibition effect was investigated for the same reservoir models to display its effect on incremental oil recovery. Furthermore, UTCOMP-EDFM was applied for hydraulic fracturing design where the performances of a simple and a complex fracture networks were evaluated in reservoirs with different rock matrix permeabilities. Accordingly, it was shown that a complex network is an ideal design for a very low permeability reservoir, while a simple network results in higher recovery when the reservoir permeability is moderate. Finally, UTGEL-EDFM was employed to optimize a conformance control process. Different injection timings and different gel concentrations were selected for water-flooding processes and their impact on oil recovery was evaluated henceforth. / text

Spontaneous imbibition plays a very important role in the displacement mechanism of non-wetting fluid in naturally fractured reservoirs. We developed a new 2D two-phase finite element numerical model, as available commercial simulators cannot be used to model small-scale experiments with different boundary conditions as well as complex boundary conditions such as fractures and vugs. Starting with the basic equation of fluid flow, we derived the non-linear diffusion saturation equation. This equation cannot be put in weighted-integral weak variational form and hence Rayleigh-Ritz finite element method (FEM) cannot be applied. Traditionally, the way around it is to use higher order interpolation functions and use Galerkin FEM or reduce the differentiability requirement and use Mixed FEM formulation. Other FEM methods can also be used, but iterative nature of those methods makes them unsuitable for solving large-scale field problems. But if we truncate the non-linear terms and decouple the dependent variables, from the spatial as well as the temporal domains of the primary variable to solve them analytically, the non-linear FEM problem reduces to a simple weighted integral form, which can be put into its corresponding weak form. The advantage of using Rayleigh-Ritz method is that it has immediate effect on the computation time required to solve a particular problem apart from incorporating complex boundary conditions. We compared our numerical models with the analytical solution of this diffusion equation. We validated the FDM numerical model using X-Ray Tomography (CT) experimental data from the single-phase spontaneous imbibition experiment, where two simultaneously varying parameters of weight gain and CT water saturation were used and then went ahead and compared the results of FEM model to that of FDM model. A two-phase field size example was taken and results from a commercial simulator were compared to the FEM model to bring out the limitations of this approach.

In recent years, wireline temperature profiling methods have evolved to offer new insight into fractured rock hydrogeology. An important advance in temperature logging makes use of boreholes temporarily sealed with flexible impervious fabric liners so that the water column is static and effects of cross-connection are eliminated. For this project a characterization technique was developed based on combining fibre optic distributed temperatures sensing (DTS) with active heating within boreholes sealed with underground liners. DTS systems provide a temperature profiling method that offers improved temporal resolution when compared with wireline trolling based techniques. The ability to collect temperature profiles rapidly in time can improve understanding of transient processes. In this study the advantage of a sealed borehole environment for temperature investigations is demonstrated. Evidence for identifying active groundwater flow under natural gradient conditions using DTS heat pulse testing is presented through a comparison with high resolution geologic logging and hydraulic datasets.

Groundwater is an important water resource that must be protected from potential contamination due to anthropogenic activities such as industrial production and agriculture. It is necessary to understand the presence, movement, and persistence of contaminants in aquifers to develop adequate protection plans. Fractured bedrock aquifers with thin overburden cover are very sensitive to contamination, and little is known about transport processes from the ground surface to depth in this setting. Thus, this research was undertaken to improve the understanding of anthropogenic impacts on water quality in a natural fractured bedrock aquifer with minimal overburden protection. This was accomplished through a field-based investigation conducted in an agricultural setting near Perth, Ontario, Canada. The temporal and spatial variations of several contaminants and indicators (including nitrate, E. coli and polybrominated diphenyl ethers) were examined. A unique infiltration tracer experiment was also conducted to simulate the transport of solutes from the ground surface to wells. Results showed that nitrate concentrations were consistent on a daily scale, but varied monthly. In contrast to nitrate, greater bacterial (E. coli) variability was observed daily. E. coli was not identified in some locations for several months. The temporal variability of concentrations is an important consideration for those consuming groundwater in this setting, as concentrations may be acceptable one month while unsuitable another month (or even another day for fecal bacteria). Annual groundwater monitoring will likely not capture maximum concentrations and thus may not protect human health. Polybrominated diphenyl ethers (flame retardants), which had not been previously measured in groundwater, were detected in the study aquifer at concentrations greater than observed in surface water bodies. It is evident that additional surveys of PBDE concentrations in groundwater are warranted. The infiltration tracer experiment showed that solute transport from the ground surface through thin soil to wells in fractured bedrock can be extremely rapid (on the order of hours) although very complex. This is an important consideration for private and municipally owned drinking water systems that draw water from shallow bedrock aquifers. The results of this research demonstrate that protecting water at the source is imperative in order to preserve water quality in sensitive fractured bedrock aquifers with minimal overburden cover. / Thesis (Ph.D, Civil Engineering) -- Queen's University, 2009-10-25 21:37:21.418

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Fluid flow process in fractured reservoirs is controlled primarily by the connectivity of fractures. The presence of fractures in these reservoirs significantly affects the mechanism of fluid flow. They have led to problems in the reservoir which results in early water breakthroughs, reduced tertiary recovery efficiency due to channeling of injected gas or fluids, dynamic calculations of recoverable hydrocarbons that are much less than static mass balance ones due to reservoir compartmentalization, and dramatic production changes due to changes in reservoir pressure as fractures close down as conduits. These often lead to reduced ultimate recoveries or higher production costs. Generally, modeling flow behavior and mass transport in fractured porous media is done using the dual-continuum concept in which fracture and matrix are modeled as two separate kinds of continua occupying the same control volume (element) in space. This type of numerical model cannot reproduce many commonly observed types of fractured reservoir behavior since they do not explicitly model the geometry of discrete fractures, solution features, and bedding that control flow pathway geometry. This inaccurate model of discrete feature connectivity results in inaccurate flow predictions in areas of the reservoir where there is not good well control. Discrete Fracture Networks (DFN) model has been developed to aid is solving some of these problems experienced by using the dual continuum models. The Discrete Fracture Networks (DFN) approach involves analysis and modeling which explicitly incorporates the geometry and properties of discrete features as a central component controlling flow and transport. DFN are stochastic models of fracture architecture that incorporate statistical scaling rules derived from analysis of fracture length, height, spacing, orientation, and aperture. This study is focused on developing a methodology for application of DFN to a shale gas reservoir and the practical application of DFN simulator (FracGen and NFflow) for fracture modeling of a shale gas reservoir and also studies the interaction of the different fracture properties on reservoir response. The most important results of the study are that a uniform fracture network distribution and fracture aperture produces the highest cumulative gas production for the different fracture networks and fracture/well properties considered.