Successful petrophysical evaluation and stimulation treatments with horizontal drilling and hydraulic fracturing enable the economic development of shale gas reservoirs. Detailed evaluation of shale gas reservoirs before and after stimulation treatments is a prerequisite to increase efficiency and effectiveness of shale gas development. Determination of organic maturity, porosity and original gas in place remains a challenge using traditional petrophysical models due to the complex pore networks and ultra-low permeability of shale. On the basis of a petrophysical model for shale gas reservoirs (
Our petrophysical model for shale gas reservoirs is partitioned into organic matter, clay and non-clay minerals in the solids, adsorbed and free gas, together with capillary-bound, clay-bound and mobile water in the pore space. Vitrinite reflectance is computed in relation to the level of organic maturity (LOM) and kerogen density. Total organic carbon (TOC) is calculated using the Passey method (
The methods are successfully applied to a field case in Marcellus shale. TOC (wt.%) calculated by (sonic-density)/resistivity overlay methods for Marcellus Shale are 9.73% and 6.32%, respectively. TOC correlates directly to porosity and adsorbed gas in place occupied within the organic matter. For Marcellus shale, average density and sonic porosities are 6.25% and 3.46%, respectively. The comparison of Young’s modulus and the minimum in-situ stress values between Marcellus shale and adjacent formations are used for the determination of the stimulation interval in the Marcellus Formation. Sonic and density logging suggest 2.22 BCF and 4.10 BCF as technically recoverable reserves with an 8% recovery factor. These results from Marcellus shale provide an improved understanding of economic development of unconventional reservoirs.
Depth matching well logs acquired from multiple logging passes in a single well has been a longstanding challenge for the industry. The existing approaches employed in commercial platforms are typically based on classical cross-correlation and covariance measures of two signals, followed by manual adjustments. These solutions do not satisfy the rising demand to minimize user intervention to proceed towards automated data interpretation. We aimed at developing a robust and fully automatic algorithm and workflow for depth matching gamma-ray logs, which are commonly used as a proxy to match the depth of other well logs measured in multiple logging passes within the same well. This was realized by a supervised machine-learning approach through a fully connected neural network. The training dataset was obtained by manually labeling a limited set of field data. As it is unrealistic to expect a perfect model from the initial training with limited manually labeled data, we developed a continuously self-evolving depth-matching framework. During the use of depth-matching service, this framework allows taking the user input and feedback to further train and improve the depth-matching engines. This is facilitated by an automatic quality-control module for that we developed a dedicated metric by combining a few different algorithms. We use this metric to assess the quality of the returned results from the depth-matching engine. The users review the results and do manual adjustments if some intervals are not ideally depth matched by the engine. Those manual adjustments can be used to further improve the machine-learning model. A well-designed framework enables automatic and continuous self-evolving of the depth-matching service.
A key aspect of the developed framework is its generalization potential because it is independent of the signal type. It could be easily extended for other log types, especially when the correlation thereof is not obvious, provided that a sufficiently large volume of labeled data is available. This framework has been prototyped and tested on field data.
Reservoir depletion can induce substantial changes in the stress state of the rock. The coupled interaction between the pore fluid pressure and rock stress will then alter the reservoir permeability, which in turn reversely affects the productivity index of the production well. A new nonlinear analytical solution is developed for the drawdown-dependent productivity index of reservoirs under steady-state flow. Biot's theory of poroelasticity is used to derive the depletion-induced changes in the reservoir rock porosity and permeability. The well-known Mindlin's solution for a Nucleus of Strain in a semi-infinite elastic medium is applied as Green's function and integrated over the depleted volume of reservoir rock to obtain the 3D distribution of stress and volumetric strain distributions. The fluid transport equation is nonlinearly coupled to the solid mechanics solution via the stress-dependent permeability coefficients. A perturbation technique is applied to mathematically treat the described nonlinearity to solve for the coupled equations of pore fluid flow and rock stress under steady-state flow. The good match between the obtained analytical approximations for productivity index and the numerical solutions verifies the correctness and robustness of the proposed model.
Results indicate and confirm the expected strong dependency of the well productivity index to the drawdown magnitude as well as the poroelastic constitutive parameters of the reservoir rock, with the highest sensitivity to drained bulk modulus, followed by the reservoir depth and solid-grain modulus. The lowest PI sensitivity is to the pore fluid modulus and Poisson's ratio. The resulting productivity index is found out to be drawdown-dependent, which can render values substantially different than the productivity index estimate from the conventional flow-only analysis. The presented estimates for the related nonlinear productivity index can be readily used by the practicing engineers.
This work proposes a novel boundary-element based approach to model fluid transport in unconventional shale gas reservoirs with complex hydraulic fracture networks. The fluid flow model employed in this work considers multiple fluid transport mechanisms identified in in gas transporting process in shale nanopores including diffusion, sorption Kinetics, Knudsen diffusion, and sorbed-phase surface diffusion. Accordingly, two governing partial differential equations (PDEs) are written for free and sorbed gases. In the proposed method, boundary integral formulations are analytically derived using the fundamental solution of the Laplace Equation for two governing nonlinear PDEs and Green's second identity. The domain integrals considering the nonlinear terms due to multi-mechanism effects, are transformed into boundary integrals employing the dual reciprocity method (DRM). The resulting boundary integral equations for free and sorbed gas later are solved in terms of a series of discrete nodes after coupling with fracture flow model. The validity of proposed solution is verified using several case studies through comparison with a commercial finite-element numerical simulator COMSOL.
Tian, Jianwei (The University of Western Australia) | Liu, Jishan (The University of Western Australia) | Elsworth, Derek (The Pennsylvania State University) | Leong, Yee-Kwong (The University of Western Australia) | Li, Wai (The University of Western Australia) | Zeng, Jie (The University of Western Australia)
Heterogeneous pore structure is critically important for unconventional gas recovery. In this paper, a dynamic fractal permeability model is proposed to investigate the interplay between heterogeneous pore structures and gas transport for coal seam gas reservoir. In this model, pore diameter and fractal dimension of pore size distribution are dynamically changing as a result of the variation of effective stress. Besides, based on fractal approach, a new Klinkenberg coefficient that dynamically changes with pore pressure is employed to incorporate the non-Darcy effect. This dynamic permeability model is applied to couple Multiphysics in coal seam gas recovery process. The impacts of these fractal parameters on permeability evolution are explored through a benchmark reservoir simulation. The numerical results exhibit good agreements with experimental data. The simulation results indicate that: (1) the dynamic permeability model matches better with experimental data than other homogeneous models, especially in low-pressure stage; (2) reservoir with larger initial fractal dimension is more sensitive to pressure depletion; (3) fractal dimension would change more dramatically when initial porosity is relatively smaller; (4) Klinkenberg coefficient increases with the decreasing of reservoir pore pressure during gas depletion. In summary, the dynamic permeability model predicts permeability evolution well in gas production process and provide some fundamental insights into the implications of reservoir heterogeneity on gas transport in reservoir simulation.
With the natural gas depletion, there is an increasing need for the exploration of unconventional natural gas, unconventional gas is typically regarded as a substitute that can relieve energy supply shortage. Permeability is the dominant factor that controls unconventional natural gas production. Therefore, it is significant to understand the mechanisms of permeability evolution and the associated influential factors. Notably, coal reservoir exhibits multi-scale heterogeneity, and pore size spans from micrometer to nanometer, which affects gas transport and storage capability substantially.
The heterogeneous pore structure of coal reservoir is characterized by multiscale pore size distribution (PSD) and the tortuous flow channel. Knudsen number ( Kn ) is defined as the ratio between the molecular free path and characteristic length, which is usually applied to describe flow regimes. The gas flow regimes include viscous flow ( Kn < 0.001 ), slip flow ( 0.001 < Kn 0.1 ), transitional flow ( 0.1 < Kn < 10 ) and free molecular flow ( Kn > 10 ). According to the definition of Knudsen number, pore size distribution determines the flow regimes in micropores when pore pressure remains constant. Therefore, the pore structure of coal has a significant impact on the apparent permeability of coal matrix. Different distribution functions have been employed to study the effect of PSD on apparent permeability, demonstrating that permeability is highly sensitive to the variation of the distribution function (Tian et al. 2017, Civan 2002). When the proportion of micropores is larger, the specific surface will increase, which will provide much more adsorption volume for coal seam gas (Tian et al. 2017). The original gas in place (OGIP) and corresponding sorption-induced swelling can be influenced substantially. For coal seam at different depths, coal swells or contracts greatly depend on PSD (Yang et al. 2010). Except for porosity, tortuosity of pore structure is an essential parameter for permeability prediction, which reflects the ratio between actual flow length and characteristic length of coal sample. According to the Kozeny-Carman model, there is a negative correlation between permeability and tortuosity(Walsh and Brace 1984). The theoretical investigation indicates that large tortuosity can increase the resistance of gas transport (Wang et al. 2017).
We show that nitrogen flooding can double matrix permeability of gas shales. In laboratory experiments, nitrogen gas increased permeability in the bedding-perpendicular and bedding-parallel directions by 206% and 234%, respectively. Experiments are performed at constant stress, pore pressure, and temperature. We build a model to show that the permeability enhancement is controlled by the sorptive strain, pore geometry, and the spacing-to-aperture ratio. This work addresses how an organic-poor shale can experience large permeability changes driven by sorption induced strains. We plot methane and helium permeability curves as a function of pore pressure to isolate the portion of permeability evolution controlled by sorption. We independently build strain curves to solve for the sorptive strain and find good agreement between these two methods. This work demonstrates that matrix permeability in gas shales can be doubled, which suggests that ultimate recovery can be improved as well.
Shale is a sedimentary rock composed primarily of silica, calcite, clays, and organic matter. Within the matrix, these individual mineral components form thin laminae separated by fracture planes which allow for fluid flow. The role of adsorption in shales has been a topic of great interest in both the scientific and industrial community, as in situ methane is adsorbed within the organic pore space. Adsorption in shales can account for up to half of the gas storage—in the case of low organic content, illite may be responsible for the additional sorptive storage (Lu et al. 1995).
Zeng, Jie (The University of Western Australia) | Li, Wai (The University of Western Australia) | Liu, Jishan (The University of Western Australia) | Leong, Yee-Kwong (The University of Western Australia) | Elsworth, Derek (The Pennsylvania State University) | Tian, Jianwei (The University of Western Australia) | Guo, Jianchun (Southwest Petroleum University)
After performing hydraulic fracturing treatments in shale reservoirs, the hydraulic fractures and their adjacent reservoir rocks can be damaged. Typically, the following fracture damage scenarios may occur: (1) choked fractures with near-wellbore damage; (2) partially propped fractures with unpropped or poorly propped sections within the fractures; (3) fracture face damage; and (4) multiple damage cases. The basic equations of fracture skin factors, which are widely used to depict fracture damage, are derived under steady-state conditions. They are not accurate when the damaged length is relatively long and are not applicable for multiple fracture damage and partially propped fractures. In this paper, a new composite linear flow model is established considering all above-mentioned fracture damage mechanisms, complex gas transport mechanisms, and the stimulated reservoir volume (SRV) of shale gas reservoirs.
The matrix model is modified from de Swaan-O's spherical element model considering the slip flow, Knudsen diffusion, surface diffusion, and desorption. Natural fractures are idealized as a thin layer that evenly covers the matrix. The reservoir-fracture flow model is extended from the seven-region linear flow model with four additional sub-regions to handle single and multiple fracture damage mechanisms. Specifically, the inner reservoir region near the primary hydraulic fracture is treated as the SRV where the secondary fracture permeability is higher than that of other unstimulated dual-porosity regions and obeys a power-law decreasing trend due to the attenuate stimulation intensity within the SRV. The flows in different regions are coupled through flux and pressure continuity conditions at their interfaces.
This model is validated by matching with the Marcellus Shale production data. And the degraded model's calculation matches well with that of the seven-region linear flow model validated by KAPPA software. Type curves with five typical flow regimes are generated and sensitivity analyses are conducted. Results indicate that the presence of the SRV diminishes pressure and derivative values in certain flow regimes depending on the SRV properties. Fracture face damage, choked fracture damage, and partially propped fractures all control specific flow regimes but the fracture face damage shows the smallest influence, only dominating the late fracture linear flow regime and the matrix-fracture transient regime. In the multiple fracture damage case, some typical flow regimes can be easily identified except the partially propped fractures. The field application example further ensures the applicability in dealing with real field data.
Zhang, Miao (The Pennsylvania State University) | Chakraborty, Nirjhor (The Pennsylvania State University) | Karpyn, Zuleima (The Pennsylvania State University) | Emami-Meybodi, Hamid (The Pennsylvania State University) | Ayala, Luis (The Pennsylvania State University)
Nano-scale pores and a dual storage mechanism shared between free and adsorbed gas make the transport behavior in shale gas reservoirs very different from conventional macropore reservoirs. This work explores a straightforward model for the gas transport behavior in shale nanopores, which couples sorption, diffusion, and sorbed-phase surface diffusion phenomena. The model combines two governing equations for free and sorbed gas phase transport processes in nanopores, respectively: a diffusion-based equation for free gas phase transport, and a surface-diffusion equation for the sorbed phase. Mass transfer between the two phases is quantified by kinetic models of sorption. The two governing equations are solved simultaneously using finite element methods (FEM). Model performance is successfully validated by closely matching density propagation profiles of a gas transport experiment obtained by quantitative X-ray computerized tomography (CT) imaging for a Marcellus shale sample. Transport-related parameters estimated from history matching are shown to be consistent with literature data.
We report experimental research on frictional strength and stability properties of shale fractures during slip. Longmaxi shale, Green River shale and Marcellus shale are selected for constant-velocity and velocity-stepping fracture shear experiments. Combing with theoretical analysis, micro controlling mechanism of mineralogy on frictional strength and stability properties of shale fractures is discussed. Results indicate that the fracture friction-stability relationship is largely affected by shale mineralogy. Frictional strength of shale fractures increases when tectosilicate content increases and phyllosilicate content decreases; during velocity-stepping experiments, three kinds of shale show velocity-strengthening behavior, which means an aseismic creep tends to occur; with the increase content of tectosilicate, shale fractures tend to have seismic slip while with the increase of phyllosilicate content, stable aseismic creep happens.
With the advances in horizontal drilling and multi-stage fracturing technologies, shale gas production has a substantial growth not only in North America, but also in other areas around the world (Jia et al., 2018; Wu et al., 2017). However, as the basic stimulation method to enhance shale gas recovery, hydraulic fracturing is implemented for almost every shale gas wells. After hydraulic fracturing operations, large-scale waste water re-injection has been linked to seismic activities (Bao and Eaton, 2016; Ellsworth, 2013; Elsworth et al., 2016), which has raised public concerns and makes hydraulic fracturing prohibited in many areas across the world.
The large-scale injection of waste water generates overpressures and decreases effective normal stresses which leads to reactivation of pre-existing faults and fractures in formations (Ellsworth, 2013), which is shown in Fig 1. In addition, the fracturing operations induced fractures may also be the source for seismic activities. Hence, the stability of pre-existing and induced fractures will decide whether seismic activities happen.
Fig. 1. Mechanism of induced seismicity by large-scale water re-injection. Natural fractures and hydraulic fracturing induced fractures may be re-activated by overpressure caused by fluid injection.
Xu, Jianchun (China University of Petroleum) | Sun, Baojiang (China University of Petroleum) | Zhang, Wei (The Pennsylvania State University) | Cheng, Hongjie (Xinjiang Oilfield Company) | Fu, Weiqi (China University of Petroleum)
Numerical simulation of well production performance for tight oil/gas reservoirs is a hot issue during recent years. Embedded discrete facture model (EDFM) is an effective numerical simulation tool as its advantages and becomes popular. Now it is widely used in multistage fractured horizontal well performance prediction. In this paper, we will extend EDFM to study the well production performance when considering Pre-Darcy flow. Firstly, the two phases flow model is established. The conservation equations are derived for different media, i.e., fracture and matrix. For the flow in fracture, the Darcy's law is used. In the matrix, the Pre-Darcy flow is considered. Then, the solution workflow is showed and the verification is presented. The simulation results of the extended model are compared with that of local grid refined (LGR) method. Finally, the test cases are presented. We show the difference of oil/water production rate when considering Darcy flow and Pre-Darcy flow. The pressure and saturation distribution are also compared. The results show big difference will happen when using different flow model.