Relative permeability (kr) functions are among the essential data required for the simulation of multiphase flow in hydrocarbon reservoirs. These functions can be measured in the laboratory using different techniques including the steady state displacement technique. However, relative permeability measurement of shale rocks is extremely difficult mainly because of the low/ultralow matrix permeability and porosity, dominant capillary pressure and stress-dependent permeability of these formations.
In this study, the impacts of stress and capillary end effects (CEE) on the measured relative permeability data were investigated. The steady state relative permeability (SS-kr) measurements were performed on Eagle Ford and Pierre shale samples. To overcome the difficulties regarding the kr measurements of shale rocks, a special setup equipped with a high-pressure visual separator (with an accuracy of 0.07 cc) was used. The kr data were measured at different total injection rates and liquid gas ratios (LGR). In addition, to evaluate the impacts of effective stress, the kr data of an Eagle Ford shale sample were measured at two different effective stresses of 1000 and 3000 psi.
From the experimental data, it was observed that the measured SS-kr data of the shale samples have been influenced by the capillary end effects as the data showed significant variation when measured at different injection rates (with the same LGR). This suggested that the liquid hold-up (i.e. capillary end effects) depends on the competition of capillary and viscous forces. In addition, it was shown that it is more necessary to correct the experimental kr data measured at the lower LGRs. Furthermore, different relative permeability curves were obtained when the kr data were measured at different effective stresses. This behavior was explained as the capillary pressure was expected to be more dominant at the higher effective stress.
The results from this study improve our understanding of unconventional mechanisms in shale reservoirs. It is evident that the behavior of unconventional reservoirs can be better predicted when more reliable and accurate relative permeability data are available. The outcomes of this study will be useful for accurate determination of such kr data.
Bagheri, Mohammadreza (Research Centre for Fluid and Complex Systems, Coventry University) | Shariatipour, Seyed M. (Research Centre for Fluid and Complex Systems, Coventry University) | Ganjian, Eshmaiel (School of Energy, Construction and Environment, Built & Natural Environment Research Centre, Coventry University)
The fluid pressure, the stress due to the column of the cement in the annulus of oil and gas wells, and the radial pressure exerted on the cement sheath from the surrounding geological layers all affect the integrity of the cement sheath. This paper studies the impact of CO2-bearing fluids, coupled with the geomechanical alterations within the cement matrix on its integrity. These geochemical and geomechanical alterations within the cement matrix have been coupled to determine the cement lifespan. Two main scenarios including radial cracking and radial compaction, were assumed in order to investigate the behaviour of the cement matrix exposed to CO2-bearing fluids over long periods. If the radial pressure from the surrounding rocks on the cement matrix overcomes the strength of the degraded layers within the cement matrix, cement failure can be postponed, while on the other hand, high vertical stress on the cement matrix in the absence of a proper radial pressure can lead to a reduction in the cement lifespan. The radial cracking process generates local areas of high permeability around the outer face of the cement sheath. Our simulation results show at the shallower depths the cement matrices resist CO2-bearing fluids more and this delays exponentially the travel time of CO2-bearing fluids towards the Earth's surface. This is based on the evolution of CO2 gas from the aqueous phase due to the reduction in the fluid pressure at shallower depths, and consumption of CO2 in the reactions which occur at the deeper locations.
Schumi, Bettina (OMV E&P) | Clemens, Torsten (OMV E&P) | Wegner, Jonas (HOT Microfluidics) | Ganzer, Leonhard (Clausthal University of Technology) | Kaiser, Anton (Clariant) | Hincapie, Rafael E. (OMV E&P) | Leitenmüller, Verena (Montan University Leoben)
Chemical Enhanced Oil Recovery leads to substantial incremental costs over waterflooding of oil reservoirs. Reservoirs containing oil with a high Total Acid Number (TAN) could be produced by injection of alkali. Alkali might lead to generation of soaps and emulsify the oil. However, the generated emulsions are not always stable.
Phase experiments are used to determine the initial amount of emulsions generated and their stability if measured over time. Based on the phase experiments, the minimum concentration of alkali can be determined and the concentration of alkali above which no significant increase in formation of initial emulsions is observed.
Micro-model experiments are performed to investigate the effects on pore scale. For injection of alkali into high TAN number oils, mobilization of residual oil after waterflooding is seen. The oil mobilization is due to breaking-up of oil ganglia or movement of elongated ganglia through the porous medium. As the oil is depleting in surface active components, residual oil saturation is left behind either as isolated ganglia or in down-gradient of grains.
Simultaneous injection of alkali and polymers leads to higher incremental oil production in the micro-models owing to larger pressure drops over the oil ganglia and more effective mobilization accordingly.
Core flood tests confirm the micro-model experiments and additional data are derived from these tests. Alkali co-solvent polymer injection leads to the highest incremental oil recovery of the chemical agents which is difficult to differentiate in micro-model experiments. The polymer adsorption is substantially reduced if alkali is injected with polymers compared with polymer injection only. The reason is the effect of the pH on the polymers. As in the micro-models, the incremental oil recovery is also higher for alkali polymer injection than with alkali injection only.
To evaluate the incremental operating costs of the chemical agents, Equivalent Utility Factors (EqUF) are calculated. The EqUF takes the costs of the various chemicals into account. The lowest EqUF and hence lowest chemical incremental OPEX are incurred by injection of Na2CO3, however, the highest incremental recovery factor is seen with alkali co-solvent polymer injection. It should be noted that the incremental oil recovery owing to macroscopic sweep efficiency improvement by polymer needs to be taken into account to assess the efficiency of the chemical agents.
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.
Since decades, steam-assisted oil recovery processes have been successfully deployed in heavy oil reservoirs to extract bitumen/heavy oil. Current resource allocation practices mostly involve reservoir model-based open loop optimization at the planning stage and its periodic recurrence. However, such decades-old strategies need a complete overhaul as they ignore dynamic changes in reservoir conditions and surface facilities, ultimately rendering heavy oil production economically unsustainable in the low-oil-price environment. Since steam supply costs account for more than 50% of total operating costs, a data-driven strategy that transforms the data available from various sensors into meaningful steam allocation decisions requires further attention.
In this research, we propose a purely data-driven algorithm that maximizes the economic objective function by allocating an optimal amount of steam to different well pads. The method primarily constitutes two components: forecasting and nonlinear optimization. A dynamic model is used to relate different variables in historical field data that were measured at regular time intervals and can be used to compute economic performance indicators (EPI). The variables in the model are cumulative in nature since they can represent the temporal changes in reservoir conditions. Accurate prediction of EPI is ensured by retraining regression model using the latest available data. Then, predicted EPI is optimized using a nonlinear optimization algorithm subject to amplitude and rate saturation constraints on decision variables i.e., amount of steam allocated to each well pad.
Proposed steam allocation strategy is tested on 2 well pads (each containing 10 wells) of an oil sands reservoir located near Fort McMurray in Alberta, Canada. After exploratory analysis of production history, an output error (OE) model is built between logarithmically transformed cumulative steam injection and cumulative oil production for each well pad. Commonly used net-present-value (NPV) is considered as EPI to be maximized. Optimization of the objective function is subject to distinct operating conditions and realistic constraints. By comparing results with field production history, it can be observed that optimum steam injection profiles for both well pads are significantly different than that of a field. In fact, the proposed algorithm provides smooth and consistent steam injection rates, unlike field injection history. Also, the lower steam-oil ratio is achieved for both well pads, ultimately translating into ~19 % higher NPV when compared with field data.
Inspired from state-of-the-art control techniques, proposed steam allocation algorithm provides a generic data-driven framework that can consider any number of well pads, EPIs, and amount of past data. It is computationally inexpensive as no numerical simulations are required. Overall, it can potentially reduce the energy required to extract heavy oil and increase the revenue while inflicting no additional capital cost and reducing greenhouse gas emissions.
The present study provides a comprehensive set of new analytical expressions to help understand and quantify well interference due to competition for flow space between the hydraulic fractures of parent and child wells. Determination of the optimum fracture spacing is a key factor to improve the economic performance of unconventional oil and gas resources developed with multi-well pads. Analytical and numerical model results are combined in our study to identify, analyze, and visualize the streamline patterns near hydraulic fractures, using physical parameters that control the flow process, such as matrix permeability, hydraulic fracture dimensions and assuming infinite fracture conductivity. The algorithms provided can quantify the effect of changes in fracture spacing on the production performance of both parent and child wells. All results are based on benchmarked analytical methods which allow for fast computation, making use of Excel-based spreadsheets and Matlab-coded scripts. Such practical tools can support petroleum engineers in the planning of field development operations. The theory is presented with examples of its practical application using field data from parent and child wells in the Eagle Ford shale (Brazos County, East Texas). Based on our improved understanding of the mechanism and intensity of production interference, the fracture spacing (this study) and inter-well spacing (companion study) of multifractured horizontal laterals can be optimized to effectively stimulate the reservoir volume to increase the overall recovery factor and improve the economic performance of unconventional oil and gas properties.
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.
The reporting of potential resources is essential to assess the future development plan and profitability of a petroleum discovery, but if the project is under appraised and production data are absent, analysts often use analogs for preliminary estimates of technically recoverable volumes. To address this, a workflow is presented for selecting appropriate analogs for unconventional plays and using them to estimate the target play's potential. The proposed technique is demonstrated with a case study of the as-yet undeveloped Bowland Shale, which is the most prominent of the shale plays in the United Kingdom (UK) and is at the early stage of its assessment. The paper describes the current shale gas activity in the UK, highlighting the enviromental constraints placed on would-be Bowland Shale developers, which impact on drilling and production operations and stem from the geographic proximity of urban developments, infrastructure and nature, which limit the size of well pad footprint in the UK where land use is high. Studies have estimated the play's in-place resources for possible future development, but there are few estimates of its corresponding recoverable volumes due to lack of production history. At the outset, a database is created with published minimum-average-maximum ranges of key parameters such as total organic carbon, maturity level, gas filled porosity, permeability, etc. that play a major role in resources estimation and recovery potential for all unconventional plays. A comparison of triangular distributions, key parameter by key parameter, between the target shale play and the analog database, is then carried out using novel graphical and statistical methods to establish a "confidence factor" relating to the analog's viability. The most appropriate analog for the Bowland Shale is chosen from an exhaustive list of North American shale gas plays. Analytical approaches are then used to transform a model of the published type well performance of the selected analog by exchanging key model parameters with those of the target shale play. The paper shows how UK operational constraints can be statistically incorporated into the workflow and have a marked effect on the estimated recovery from the Bowland Shale.
Martins, Ana (Nederlandse Aardolie Maatschappij) | Marino, Marco (Nederlandse Aardolie Maatschappij) | Kerem, Murat (Shell Global Solutions International) | Guzman, Manuel (Shell Global Solutions International)
This paper presents the first comparison between two different injection methods for foam assisted gas lift. Useful information for operators and technology developers are also provided concerning chemical selection, testing, and deployment of this hybrid artificial lift technology in the field.
The trials have been conducted in a gas lifted oil well with severe slugging and water cut above 50% (selection criteria as per SPE-184217-MS). The surfactant was delivered through a dedicated capillary injection string during the first trial, and the effects of surfactant concentration and depth of injection were evaluated. During the second trial, the surfactant was injected into the gas lift stream at the surface. Different surfactants were utilised for both trials based on stability concerns and method of injection.
Both trialled injection methods successfully stabilized the well flow, terminating severe slugging while increasing the drawdown and delivering an increase in gross production of circa 200%. These results, together with the downhole pressure data collected during the first trial, confirm that the surfactant starts foaming only at the depth where the lift gas enters the tubing. Injecting surfactant into the lift gas stream required higher concentrations than using a dedicated injection string, difference attributable to the slightly different chemistry, but even at those higher concentrations an anti-foamer injection was not required.
Concerning the response time, the well responded in 30 to 60 minutes with capillary string injection, while 6 to 12 hours were required for injection into the lift gas stream. This suggests that the surfactant probably moves slowly down on the annulus walls as a liquid film rather than travelling in droplets dispersed in the gas phase. Based on the outcome of the two trials, it is concluded that the injection via the lift gas stream is as effective as capillary string injection, at a fraction of the initial costs, with lower maintenance requirements, while still allowing access to the well.