Recent studies have indicated that Huff-n-Puff (HNP) gas injection has the potential to recover an additional 30-70% oil from multi-fractured horizontal wells in shale reservoirs. Nonetheless, this technique is very sensitive to production constraints and is impacted by uncertainty related to measurement quality (particularly frequency and resolution), and lack of constraining data. In this paper, a Bayesian workflow is provided to optimize the HNP process under uncertainty using a Duvernay shale well as an example.
Compositional simulations are conducted which incorporate a tuned PVT model and a set of measured cyclic injection/compaction pressure-sensitive permeability data. Markov chain Monte Carlo (McMC) is used to estimate the posterior distributions of the model uncertain variables by matching the primary production data. The McMC process is accelerated by employing an accurate proxy model (kriging) which is updated using a highly adaptive sampling algorithm. Gaussian Processes are then used to optimize the HNP control variables by maximizing the lower confidence interval (μ-σ) of cumulative oil production (after 10 years) across a fixed ensemble of uncertain variables sampled from posterior distributions.
The uncertain variable space includes several parameters representing reservoir and fracture properties. The posterior distributions for some parameters, such as primary fracture permeability and effective half-length, are narrower, while wider distributions are obtained for other parameters. The results indicate that the impact of uncertain variables on HNP performance is nonlinear. Some uncertain variables (such as molecular diffusion) that do not show strong sensitivity during the primary production strongly impact gas injection HNP performance. The results of optimization under uncertainty confirm that the lower confidence interval of cumulative oil production can be maximized by an injection time of around 1.5 months, a production time of around 2.5 months, and very short soaking times. In addition, a maximum injection rate and a flowing bottomhole pressure around the bubble point are required to ensure maximum incremental recovery. Analysis of the objective function surface highlights some other sets of production constraints with competitive results. Finally, the optimal set of production constraints, in combination with an ensemble of uncertain variables, results in a median HNP cumulative oil production that is 30% greater than that for primary production.
The application of a Bayesian framework for optimizing the HNP performance in a real shale reservoir is introduced for the first time. This work provides practical guidelines for the efficient application of advanced machine learning techniques for optimization under uncertainty, resulting in better decision making.
This study is based on the premise that most of the trapped hydrocarbons can be produced, if we substitute them with another ‘acrificial’ fluid that has amplified interactions with organic pore walls, such as CO2. For the presented study, a downhole shale sample is analyzed in the laboratory to predict gas storage properties such as pore-volume, pore compressibility, and gas adsorption capacity. Then a series of pressure pulse decay measurements are performed to delineate transport mechanisms and predict stress-sensitive permeability. These coefficients are obtained as the calibration parameters of a simulation-based optimization for injection and production. Simulation model considers compositional gas flow in a deformable porous media and includes a multi-continuum porosity, with organic and inorganic pores, and micro-fractures. The experimental and simulation results show that most of the injected CO2 is adsorbed in the organic matrix and are not produced back. This is because CO2 molecules have significantly larger adsorption capacity when compared to methane. The strong adsorption of CO2 improves the release of natural gas from kerogen pores. This indicates that the separation of produced CO2 will be a minimal cost. Transport in kerogen has significant pore wall effects, and includes large mass fluxes of the adsorbed molecules by the walls due to surface diffusion. In essence, the adsorbed CO2 molecules significantly influence transport of methane. The results also show core-plug permeability is stress-sensitive due to presence of micro-fractures. Forward simulation results using optimum parameters indicate that closure stress developing near the fractures could significantly control the volume of CO2 injected. This raises operational issues on when to start injecting, and how to inject CO2. Using a simulation study of a production well with single-fracture, we show that fracture closure stress develops rapidly and production rate becomes a slave of the fracture geo-mechanics, e.g., strength of the proppants and the level of proppant embedment.
Lin, Ran (Southwest Petroleum University) | Ren, Lan (Southwest Petroleum University) | Zhao, Jinzhou (Southwest Petroleum University) | Tao, Yongfu (Exploration and Development Research Institute, Yumen Oilfield Company) | Tan, Xiucheng (Southwest Petroleum University) | Zhao, Jiangyu (Southwest Petroleum University)
Multi-stage & multi-cluster fracturing in horizontal well drilling is the core technology in for commercial exploitation of shale gas resevoir. According to vast field data, there is remarkable positive correlation relationship between stimulated reservoir volume (SRV) and shale gas production. Hence, estimating the SRV is essential for both pre-fracturing design and post-fracturing evaluation. However, the forming process of SRV involves with many complex mechanisms, making it is difficult to be simulated.
In this paper, we establish a mathematical model to estimate the SRV by simulating multiple hydraulic fractures propagate, formation stress change and reservoir pressure rise; consequently, the stress and pressure change might make natural fractures occur tensile failure or shear failure, generating a high-conductivity zone (i.e., SRV) in the shale reservoir.
To solve the model, displacement discontinuity method (DDM) is applied to simulate non-planar propagation of multiple hydraulic fractures and calculate formation stress change. Finite difference method (FDM) is used to compute reservoir pressure rise. The natural fractures failure state is determined by tensor formulae derived from Warpinski's failure theory. This SRV estimation method involves a variety of complex but crucial physical mechanisms during shale fracturing process which include unequal flow-rate distribution in different hydraulic fractures, non-planar hydraulic fractures propagation under stress interference, reservoir permeability increases with SRV expanding, two types of natural fracture failure and so on.
A field case study was performed to show the dynamic processes of hydraulic fractures propagation, reservoir permeability increase, and the SRV expansion during shale gas fracturing. Then we compared the simulation results with analytical solution, published papers and on-site microseismic monitoring data to verify our model. Finally, the influence of geological condition and engineering parameters on SRV was investigated by sensitivity analysis.
The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS.
This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers.
Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles.
This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.
Berawala, Dhruvit Satishchandra (Department of Energy and Petroleum Technology, University of Stavanger, Norway and The National IOR Centre of Norway) | Østebø Andersen, Pål (Department of Energy Resources, University of Stavanger, Norway and The National IOR Centre of Norway)
Only 3-10 % of gas from tight shale is recovered economically through natural depletion, demonstrating a significant potential for enhanced shale gas recovery (ESGR). Experimental studies have demonstrated that shale kerogen/organic matter has higher affinity for CO2 than methane, CH4, which opens possibilities for carbon storage and new production strategies.
This paper presents a new multicomponent adsorption isotherm which is coupled with a flow model for evaluation of injection-production scenarios. The isotherm is based on the assumption that different gas species compete for adsorbing on a limited specific surface area. Rather than assuming a capacity of a fixed number of sites or moles this finite surface area is filled with species taking different amount of space per mole. The final form is a generalized multicomponent Langmuir isotherm. Experimental adsorption data for CO2 and CH4 on Marcellus shale are matched with the proposed isotherm using relevant fitting parameters. The isotherm is first applied in static examples to calculate gas in place reserves, recovery factors and enhanced gas recovery potential based on contributions from free gas and adsorbed gas components. The isotherm is further coupled with a dynamic flow model with application to CO2-CH4 substitution for CO2-ESGR. We study the feasibility and effectiveness of CO2 injection in tight shale formations in an injection-production setting representative of lab and field implementation and compare with regular pressure depletion.
The production scenario we consider is a 1D shale core or matrix system intitally saturated with free and adsorbed CH4 gas with only left side (well) boundary open. During primary depletion, gas is produced from the shale to the well by advection and desorption. This process tends to give low recovery and is entirely dependent on the well pressure. Stopping production and then injecting CO2 into the shale leads to increase in pressure where CO2 gets preferentially adsorbed over CH4. The injected CO2 displaces, but also mixes with the in situ CH4. Restarting production from the well then allows CH4 gas to be produced in the gas mixture. Diffusion allows the CO2 to travel further into the matrix while keeping CH4 accessible to the well. Surface substitution further reduces the CO2 content and increases the CH4 content in the gas mixture that is produced to the well. A result of the isotherm and its application of Marcellus experimental data is that adsorption of CO2 with resulting desorption of CH4 will lead to a reduction in total pressure if the CO2 content in the gas composition is increased. That is in itself an important drive mechanism since the pressure gradient driving fluid flow is maintained (pressure buildup is avoided). This is a result of CO2 being found to take ~24 times less space per mol than CH4.
Analytically-derived criteria are presented for the orientation of fracture initiation from horizontal wellbores drilled in porous-permeable (poroelastic) media. This involves drilling-induced tensile fractures (DITFs) from non-perforated wellbores and completion-induced hydraulic fractures (CIHFs) from perforated wellbores with cylindrical perforation geometry. The criteria are developed considering the tangential stresses on two points (extremes) around the base of the perforation; one for the initiation of longitudinal fractures and another for the initiation of transverse fractures, with respect to the wellbore. In-situ stress state, wellbore pressure, and the formation's mechanical and poroelastic properties are independent variables that are shown to control the orientation of the initiated hydraulic fractures; the dependent variable.
The DITF orientation can be used to constrain the magnitude of the maximum horizontal stress; the most difficult aspect of the in-situ stress tensor to constrain. Transverse CIHF initiation only occurs over a narrow wellbore pressure-at-breakdown window, while longitudinal initiation occurs at comparatively higher wellbore pressures. However, transverse CIHF initiation occurs more frequently than transverse DITFs, because the presence of perforations aids transverse fracture initiation. The region of the in-situ stress states where transverse initiation is promoted is shown in dimensionless plots for perforated and non-perforated wellbores. Fracture initiation criteria for specific cases presented can be used to predict the orientation of fracture initiation in oilfield operations.
The orientation of CIHFs controls the productivity of hydrocarbon reservoirs. Productivity from low permeability formations is greatly improved having multiple fractures oriented transversely rather than longitudinally, relative to a horizontal wellbore. Fracture initiation often follows a plane different to the final fracture propagation plane. Stress re-orientation in the near-wellbore region may promote fracture initiation of different orientation than the orientation dictated by the far-field stresses. The range of in-situ stress states in which transverse fracture initiation is promoted increases as Biot's poroelastic coefficient,
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.
You, Junyu (Petoleum Recovery Research Center) | Ampomah, William (Petoleum Recovery Research Center) | Kutsienyo, Eusebius Junior (Petoleum Recovery Research Center) | Sun, Qian (Petoleum Recovery Research Center) | Balch, Robert Scott (Petoleum Recovery Research Center) | Aggrey, Wilberforce Nkrumah (KNUST) | Cather, Martha (Petoleum Recovery Research Center)
This paper presents an optimization methodology on field-scale numerical compositional simulations of CO2 storage and production performance in the Pennsylvanian Upper Morrow sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas. This work develops an improved framework that combines hybridized machine learning algorithms for reduced order modeling and optimization techniques to co-optimize field performance and CO2 storage.
The model's framework incorporates geological, geophysical, and engineering data. We calibrated the model with the performance history of an active CO2 flood data to attain a successful history matched model. Uncertain parameters such as reservoir rock properties and relative permeability exponents were adjusted to incorporate potential changes in wettability in our history matched model.
To optimize the objective function which incorporates parameters such as oil recovery factor, CO2 storage and net present value, a proxy model was generated with hybridized multi-layer and radial basis function (RBF) Neural Network methods. To obtain a reliable and robust proxy, the proxy underwent a series of training and calibration runs, an iterative process, until the proxy model reached the specified validation criteria. Once an accepted proxy was realized, hybrid evolutionary and machine learning optimization algorithms were utilized to attain an optimum solution for pre-defined objective function. The uncertain variables and/or control variables used for the optimization study included, gas oil ratio, water alternating gas (WAG) cycle, production rates, bottom hole pressure of producers and injectors. CO2 purchased volume, and recycled gas volume in addition to placement of new infill wells were also considered in the modelling process.
The results from the sensitivity analysis reflect impacts of the control variables on the optimum results. The predictive study suggests that it is possible to develop a robust machine learning optimization algorithm that is reliable for optimizing a developmental strategy to maximize both oil production and storage of CO2 in aqueous-gaseous-mineral phases within the FWU.
Penghui, Su (PetroChina Research Institute of Petroleum Explorationand and Development) | Zhaohui, Xia (PetroChina Research Institute of Petroleum Explorationand and Development) | Ping, Wang (PetroChina Research Institute of Petroleum Explorationand and Development) | Liangchao, Qu (PetroChina Research Institute of Petroleum Explorationand and Development) | xiangwen, Kong (PetroChina Research Institute of Petroleum Explorationand and Development) | Wenguang, Zhao (PetroChina Research Institute of Petroleum Explorationand and Development)
Interest has spread to potential unconventional shale reservoirs in the last decades, and they have become an increasingly important source of hydrocarbon. Importantly, pore structure of shale has considerable effects on the storage, seepage and output of the fluids in shale reservoirs so that reliable fractal characteristics are essential. To better understand the evolution characteristics of pore structure for a shale gas condensate reservoir and their influence on liquid hydrocarbon occurrences and reservoir physical properties, we conducted high-pressure mercury intrusion tests (HPMIs), field emission scanning electron microscopies (FESEM), total organic carbon (TOC), Rock-Eval pyrolysis and saturation measurements on samples from the Duvernay formation. Furthermore, the fractal theory is applied to calculate the fractal dimension of the capillary pressure curves, and three fractal dimensions D1, D2 and D3 are obtained. The relationships among the characteristics of the Duvernay shale (TOC, organic matter maturity, fluid saturation), the pore structure parameters (permeability, porosity, median pore size), and the fractal dimensions were investigated.
The results show that the fractal dimension D1 ranges from 2.44 to 2.85, D2 ranges from 2.09 to 2.15 and D3 ranges from 2.35 to 2.48. D2 and D3 have a good positive correlation. The pore system studied mainly consists of organic pores and microfractures, with the percentage of micropores being 50.38%. TOC has a positive relationship with porosity and D3 due to the development of organic pores. D3 has a positive correlation with gas saturation. With increased D3, median pore size shows a decreasing trend and an increase in permeability and porosity, demonstrating that D3 has a large effect on pore size distribution and the heterogeneity of pore size. In general, D3 has a better correlation with petrophysical and petrochemical parameters. Fractal theory can be applied to better understand the pore evolution, pore size distribution and fluid storage capacity of shale reservoirs.
Kutsienyo, Eusebius Junior (Petroleum Recovery Research Center) | Ampomah, William (Petroleum Recovery Research Center) | Sun, Qian (Petroleum Recovery Research Center) | Balch, Robert Scott (Petroleum Recovery Research Center) | You, Junyu (Petroleum Recovery Research Center) | Aggrey, Wilberforce Nkrumah (KNUST) | Cather, Martha (Petroleum Recovery Research Center)
This paper presents field-scale numerical simulations of CO2 injection activities in the Pennsylvanian Upper Morrow sandstone reservoir, usually termed the Morrow B sandstone, in the Farnsworth Unit (FWU) of Ochiltree County, Texas. The CO2 sequestration mechanisms examined in the study include structural-stratigraphic, residual, solubility and mineral trapping. The reactive transport modelling incorporated in the study evaluates the field's potential for long-term CO2 sequestration and predicts the CO2 injection effects on the Morrow B pore fluid composition, mineralogy, porosity, and permeability.
The dynamic CO2 sequestration model was built from an upscaled geocellular model for the Morrow B. This model incorporated geological, geophysical, and engineering data including well logs, core, 3D surface seismic and fluid analysis. We calibrated the model with active CO2-WAG miscible flood data by adjusting control parameters such as reservoir rock properties and Corey exponents to incorporate potential changes in wettability. The history-matched model was then used to evaluate the feasibility and mechanisms for CO2 sequestration. We used the maximum residual phase saturations to estimate the effect of gas trapped due to hysteresis. The coupled approach which involves the aqueous phase solubility and geochemical reactions were modelled prior to import into the compositional simulation model. The viscosities of the liquid-vapor phases were modeled based on the Jossi-Stiel-Thodos Correlation. This correlation depended on the mixture density calculated by the equation of state. The gas solubility coefficients for the aqueous phase were estimated using Henry's law for various components as function of pressure, temperature, and salinity. The characteristic intra-aqueous and mineral dissolution/precipitation reactions were assimilated numerically as chemical equilibrium and rate-dependent reactions respectively. Multiple scenarios were performed to evaluate the effects and potentials of the CO2 sequestrated within the Morrow formation. Additional scenarios that involve shut-in of wells were performed and the reservoir monitored for over 150 years to understand possible dissolution/precipitation of minerals. Changes in permeability as a function of changes in porosity caused by mineral precipitation/dissolution were calibrated to the laboratory chemo-mechanical responses.
This confirms the CO2 injection in the morrow B will alter petrophysical properties, such as permeability and porosity in short-term due to the dissolution of calcite. However, further investigation for the long-term effects needs to be conducted. Moreover, the following significant observations are extracted from the result of this study: oil recovery, total volume of CO2 due to multiple trapping mechanisms, effect of salinity, the timescale-view of the dissolution/precipitation evolution in the Morrow B sandstone.
Experiences gained from this study offers valuable visions regarding physiochemical storage induced by the CO2 injection activities and may serve as a benchmark case for future CO2-EOR projects when reactive transportations are considered.