In reservoir multiphase flow processes with high flow rates, both viscous and capillary forces determine the pore-scale fluid configurations, and significant dynamic effects could appear in the capillary-pressure/saturation relation. We simulate dynamic and quasi-static capillary pressure curves for drainage and imbibition directly in SEM images of Bentheim sandstone at mixed-wet conditions by treating the identified pore spaces as tube cross-sections. The phase pressures vary with length positions along the tube length but remain unique in each cross-section, which leads to a nonlinear system of equations that are solved for interface positions as a function of time. The cross-sectional fluid configurations are computed accurately at any capillary pressure and wetting condition by combining free energy minimization with a menisci-determining procedure that identifies the intersections of two circles moving in opposite directions along the pore boundary. Circle rotation at pinned contact lines accounts for mixed-wet conditions. Dynamic capillary pressure is calculated using volume-averaged phase pressures, and dynamic capillary coefficients are obtained by computing the time derivative of saturation and the difference between the dynamic and static capillary pressure. Consistent with previously reported measurements, our results demonstrate that, for a given water saturation, simulated dynamic capillary pressure curves are located at a higher capillary level than the static capillary pressure during drainage, but at a lower level during imbibition, regardless the wetting state of the porous medium. The difference between dynamic and static capillary pressure becomes larger as the pressure step applied in the simulations is increased. The model predicts that the dynamic capillary coefficient is a function of saturation and independent of the incremental pressure step, which is consistent with results reported in previous studies. The dynamic capillary coefficient increases with decreasing water saturation at water-wet conditions, whereas for mixed- to oil-wet conditions it increases with increasing water saturation. The imbibition simulations performed at mixed- to oil-wet conditions also indicate that the dynamic capillary coefficient increases with decreasing initial water saturation.
The proposed modelling procedure provides insights into the extent of dynamic effects in capillary pressure curves for realistic mixed-wet pore spaces, which could contribute to improved interpretation of core-scale experiments. The simulated capillary pressure curves obtained with the pore-scale model could also be applied in reservoir simulation models to assess dynamic pore-scale effects on the Darcy scale.
Hydrodynamic aquifer conditions have been described in many basins around the world since first introduced by Hubbert1 in 1953. The hydrodynamic aquifer concept in Ormen Lange has been assessed using iso-potential mapping1 and dynamic simulation of the fluid fill development (i.e. imbibition) over geological time. Simulation shows2,3 the hydro-dynamically tilted/stepping contacts depend on rate of water flow across the aquifer, stratigraphic baffling and faulting, effective aquifer area and reservoir quality (NTG and effective permeability). The role of sealing faults over geological time scale is downplayed in terms of justifying the fluid distribution. Baffling during production is, however, expected. In Ormen Lange the hydrodynamic aquifer has pushed the gas from the crest of the structure into the south of the field leaving behind a northward-thickening prism of residual gas which is imaged by a seismic DHI. Confirmation of the hydrodynamic aquifer scenario in this field was achieved after drilling an appraisal well in the north of the structure that corroborated fluids (water with residual gas) and pressures as prognosed by the hydrodynamic aquifer model.
Quality maps have been introduced as an efficient and expedient tool to select infill well placements, quality being a measure of how good an area is expected to be for production. Even though this tool is less CPU-time consuming than optimization algorithms, it still requires a significant number of flow simulations. Solving the computation time problem is even more challenging when dealing with geological uncertainty. In this case, quality maps have to be determined for several possible reservoir models, which clearly induces an increase in the number of flow simulations to be performed. In this paper, we first investigate the impact of geological uncertainty on quality maps. Then, we compare the potential of kriging and multi-fidelity meta-models for approximating quality from a reduced number of flow simulations. The main interest of the multi-fidelity technique is its ability to incorporate data at different levels of resolution. Thus, you can balance the flow simulations performed at the fine scale by flow simulations at the coarse scale. The latter being cheaper to evaluate, the computational overburden is considerably reduced. This approach turns out to be promising for the case studied.
One of the major issues with the development of unconventional ultratight shale-gas reservoirs is related to concerns about underdisplacing or overdisplacing hydraulic proppant-fracture treatments in multiple-zone completions in horizontal wells.
In recent years, a very large number of multistage propped-fracture treatments in horizontal wells in ultratight shale-gas reservoirs have been overdisplaced to obtain a clean wellbore and avoid problems with the hardware (especially pump-down plugs) used for rapid multizone completions. Because cleanout treatments can usually be avoided by these overdisplacements, multiple treatment stages can be performed more quickly, which saves time and minimizes other added costs. However, this practice might result in poor communication between the propped fractures placed in the reservoir and the wellbore.
In some situations, such as when the rock strength is sufficient to prevent closure of nonpropped fracture areas, overdisplacing a treatment could result in a very high conductivity region at the wellbore. There is certainly a limit to the length of an unpropped fracture that could stay open for a significant time. This mechanism is similar to what has been seen in some wells with proppant production, where well productivity has increased following proppant production. Proppant production might create some open channels in the proppant pack near the perforations that remain open.
This paper discusses current overdisplacement practices and tries to address if and when overdisplacing fractures in shale- or tight-gas reservoirs could have a net positive or a negative effect on production.
In the not-too-distant past, hydraulic fracturing was thought to accomplish one or more of the following four objectives: 1) to improve the inflow capacity near the wellbore by bypassing drilling- or production-induced damage around the wellbore, 2) to alter the flow geometry from radial flow to linear flow in lower-permeability formations by placing a long, high-flow-capacity fracture system, 3) to aid with secondary recovery operations by increasing the capacity of water injection wells, possibly in combination with high-capacity flow channels in producing wells, to increase flow efficiency, and 4) to create low-pressure, high-fluid-injection-capacity wells for brine and industrial-waste-disposal purposes (Howard and Fast 1970).
It was the realization of the fact that a long, high-flow-capacity fracture system would provide a low-resistance flow path to the wellbore and maximize the available reservoir energy that made the second objective more important, from a commercial point of view—allowing operators to economically exploit low-permeability hydrocarbon-bearing reservoirs. The theoretical basis was originally formulated for this by several authors (van Poollen et al. 1958; McGuire and Sikora 1960; Prats 1961; Tinsley et al. 1969; Holditch and Morse 1970) whereby the productivity ratio of a hydraulically fractured well compared to a nonfractured well was directly proportional to the ratio of fracture flow capacity (conductivity) compared to formation productive capacity, both expressed in md-ft, in combination with a certain fracture-length-to-drainage-radius ratio.
We used a commercial reservoir simulator to study first the dissipation of aqueous drilling fluid filtrate invasion around a cased observation well in an oil-saturated formation under the action of capillary pressure, and then the interaction of a waterflood front with the cased well and remaining invaded zone. Hysteretic behavior of the capillary pressure and relative permeabilities is critically important to these processes and is taken into account using the Killough model, with the various bounding drainage and imbibition curves computed from a pore network model.
Filtrate invasion into a hydrocarbon formation influences the readings of well logging tools. Although this phenomenon has been known, and corrected for, for many years, uncertainty remains with regard to the long-time behavior of invasion around observation wells where no flow in or out of the formation occurs after completion, and also with regard to the influence of formation wettability. We find that after sufficient time the invaded zone dissipates completely in a water-wet formation, but some invasion always remains in the oil/mixed-wet case. Non-wetting-phase trapping, manifested through relative permeability hysteresis, is the cause. Because trapping affects the values and the end points of the relative permeability curves, a waterflood front passing across an observation well is more distorted in the oil/mixed-wet case. The simulation results allow us to understand how logging tool measurements made in cased observation wells are influenced by drilling fluid invasion and will therefore lead to improved interpretation. This study shows strong links between the wettability of the formation and persistence of invaded zone saturation and between invaded zone saturation and the distortion of subsequent flood fronts.
The work presented in this paper analyzes surface and downhole microseismic data for a horizontal well in the Woodford Shale in Oklahoma and compares those results with calibrated hydraulic fracture modeling. Hydraulic fracture models were created for each of five stages with a three-dimensional modeling software, incorporating available petrophysical data in order to match the recorded treatment pressure and the fracture geometry obtained from the microseismic data. Further analysis investigated the congruency of the downhole and the surface microseismic data, what differences they produced in a match if used exclusively, the influence of the number of events on the fracture geometry obtained from the microseismic data, the error of event location, the degree of complexity of the created fracture network, and the relationship between the magnitude of events and the time and location of their occurrence.
The fracture models produced good matches for both pressure and fracture geometry but showed problems matching the fracture height due to cross-stage fracturing into parts of the reservoir that were already stimulated in a previous stage. Surface and downhole microseismic data overlapped in certain regions and picked up on different occurrences in others, giving a more complete picture of microseismic activity and fracture growth if used together. However, they deviated in terms of vertical event location with surface data showing more upward growth and downhole data showing more downward growth. In general, the downhole microseismic data showed that the stimulation treatment was successful in creating a fairly complex hydraulic fracture network for all stages, with microseismic recordings making flow paths visible governed by both paleo and present day stresses. Plots showing the speed of event generation, the cumulative seismic moment, and the event magnitude versus the event-to-receiver-distance identified interaction with pre-existing fault structures during Stages III and V.
The Statfjord field entered into the blow down phase after 30 years of production. Production of injection gas and gas liberated from residual oil is the main production target in this phase. In some areas, the gas cap has been produced and the wells are producing mainly water until the solution gas is mobilized. These wells have gone through large changes in gas-liquid-ratio (GLR) and water-cut (WCT). Production tests from wells located in such areas have been used when analyzing the ability of multiphase-flow correlations to model vertical lift performance (VLP). Accurate modeling of the VLP is critical to predict a realistic production rate during the blow down phase.
Measured wellhead (THP) and downhole pressures from about 80 production tests, from four wells, were used to analyze the accuracy of VLP correlations at widely varying flow conditions (GLR, WCT, and THP). Altogether 17 multiphase pressure drop correlations incorporated in the program Prosper were tested by comparing observed and calculated downhole pressures.
Based on the production tests the ability of the different correlations to predict the VLP varies with the following top 4: Hagedorn Brown, Petroleum Experts, Petroleum Experts 2, and Petroleum Experts 3. These correlations are recommended if no measured data is available.
In general a somewhat low pressure drop is predicted at low gas-liquid ratio (GLR), and a somewhat high pressure drop is predicted at high GLR. After tuning, accurate predictability was observed for the different correlations for limited ranges in GLR e.g. 50-300 Sm3/Sm3. However, for larger ranges in GLR it was not possible to achieve an accurate VLP correlation, even after tuning. Hagedorn Brown and Petroleum experts seem to be the most accurate correlations for a wide range of producing GLR.
The error in the predicted production performance when a single VLP correlation is used can be substantial for highly productive wells with large variations in producing GLR. It is recommended to shift the tuning following the GLR development.
Calculating the pressure drop in the production tubing is important for well design, production optimization, and for generation of production prognosis. Many multiphase flow correlations are proposed. Still, none of them are proven to give good results for all conditions that may occur when producing hydrocarbons (Pucknell et al. 1993). Analysis of available correlations is often the best way to determine which one to use (Brill and Mukherjee 1999). Some will be good for liquid wells, whereas others for gas. Most of the correlations are to some degree empirical and will thereby be limited to conditions of which the correlations are based on (Pucknell et al. 1993).
Kashagan is a super giant offshore carbonate field which was discovered in 2000 by a consortium of oil companies (currently, affiliates of): ExxonMobil, ENI, Shell, TOTAL, Conoco-Phillips, INPEX and KazMunaiGaz. The field is located in an environmentally sensitive area of the North Caspian Sea. The field is a deep, large structural relief, over pressured, isolated, carbonate build-up with a high-permeability, karstified and fractured rim and relatively low-permeability platform interior. The field contains a sour, undersaturated light oil with a large gas content. High pressure miscible gas injection is planned for oil recovery enhancement, as well as sulfur management.
No-one doubts the importance of flow assurance in offshore projects in particular. Moreover, it is now well known that gas injection operations require the evaluation of asphaltene deposition risk. The consortium has undertaken extensive evaluations to ascertain the likelihood of any flow assurance risks from subsurface to surface. During the asphaltene risk evaluation, many bottomhole samples have been collected and analyzed for asphaltene content, asphaltene onset pressure (AOP), and SARA (saturates, aromatics, resins and asphaltenes). These continuous analysis efforts have revealed some anomalous results such as AOP being detected from some fluid samples while not being detected from others.
The apparently inconsistent AOP results are critical to understand how to guide flow assurance measures. Therefore, all available asphaltene data were re-assessed in all their aspects to attempt to clarify asphaltene risk. This paper presents a multidisciplinary approach where a synergy between reservoir engineering and geoscience (geology and geohistory) has been developed to explain AOP results for this complex fluid. The results should help flow assurance specialists to better define the asphaltene operating envelope, which will be used for reservoir and production operations optimization. In addition, these results should be useful for optimizing data-surveillance, flow assurance, and for defining new sample acquisition plans. These findings may also be helpful to minimize future sampling and fluids analysis while achieving reliable flow assurance. The paper will show examples of the related flow assurance analyses, and the geological information which were incorporated in the study, resulting in a detailed asphaltene matrix risk profile for this reservoir.
CO2 injection is a proven EOR (enhanced oil recovery) method, which has been extensively applied in the field. CO2 promotes oil recovery through a number of mechanisms including; CO2 dissolution, viscosity reduction, oil swelling, and extraction of light hydrocarbon components of crude oil. One of the main advantages considered for CO2 injection is that it can develop miscibility with most of light crude oils at a pressure lower than what would be required for other gases. Miscibility development is a function of reservoir pressure, temperature and also oil composition. In water flooded oil reservoirs, water can adversely affect the performance of CO2 injection as it reduces the contact between oil and CO2. However, CO2 will be able to dissolve into water and diffuse from water into the oil. The dynamic interplay between these various mechanisms is complicated and cannot be captured by existing models and simulations.
In this paper we present the highlights of the results of a series of visualization (micromodel) experiments performed using three different crude oils. CO2 injection was carried out to investigate the pore-scale interactions between CO2, crude oil and water inside the porous medium under liquid, vapour and super-critical conditions. In particular, we reveal a new mechanism that can lead to the recovery of the disconnected oil ganglia that do not come to direct contact with injected CO2. Our results reveal that, under certain conditions, a new phase can be formed in trapped oil ganglia and grows in size and can eventually connect the ganglia to the flowing CO2 stream and lead to their production. The increase in the size of the new phase continues without limit as long as CO2 injection continues and is much more than what can be achieved by the swelling of the oil due to CO2 dissolution. In the injection strategies where CO2 injection is associated or followed by water injection, e.g. CO2-WAG or CO2-SWAG, formation of the new phase can also divert the flow of water towards the unswept regions of the porous media and lead to additional oil recovery.
Intelligent Wells are distinguished from conventional wells by being equipped with downhole sensors to monitor the Inflow Control Valves (ICVs) to control the (multiple) zonal flow rates. The data from the downhole sensors monitors the properties of the fluid flowing into the well from the reservoir at a zonal or a well level. The sensor data is analysed to provide the necessary information for the ICVs to be operated in the optimum manner i.e. to increase the hydrocarbon recovery and prevent unwanted fluid production.
This objective is simply stated, but the optimisation calculations required to identify the optimum ICV settings necessitates the repetitive solution of a complex, non-linear problem. Several commercial software providers have made such optimisation algorithms available to the industry to perform this task. However, experience has shown that challenges still arise when they are applied to large, complex models even though these algorithms work well on many simple cases. This is especially true when the optimisation algorithm is combined with a large, multi-well simulation model of multiple reservoirs with a complex, surface production network that is typical of those used today by operators to study real-field cases prior to field development.
Inclusion of the optimisation algorithm not only dramatically increases the calculation time (up to 50 times when compared with the equivalent run without such optimisation); but also stability and convergence problems give additional increases in the running time. More importantly, the combined software will sometimes simply stop, due to erroneous control parameters being provided by the optimisation algorithm. The optimisation algorithm may also return unrealistic results at random time intervals, a problem that can lead to unnecessary complications as it may not be immediately recognised. Such problems are particularly acute if the software is performing multiple realisations, for example when it is being applied to analyse the impact of a multiple field development scenarios or when studying how uncertainty in the reservoir's dynamic and static properties affect the field's production performance.
This paper will present a novel method based on the direct search algorithm for implementing an ICV control strategy. This method was chosen since it is not affected by the convergence problems which have caused many of the difficulties associated with previous efforts to solve our non-linear optimisation problem. Our control strategy will use the current, zonal inflow rate and water cut data to identify the optimal ICV choke positions. The availability of this data reduces the number of possible choke positions that have to be evaluated at each time step by the simulator. Run times similar to the base case are potentially possible while, equally importantly, the optimal value identified is similar to the value returned by the other published optimisation methods referred to above.
This paper outlines the assumptions made and, after exploring the method's use in two single well models for reactive control of oil production from intelligent wells completed with discrete ICVs, its application to a large, reservoir simulation model will be illustrated. The latter application could be implemented rapidly, unlike some other optimisation software, because "tuning?? of the model and/or the method was not required; the control algorithm being always convergent, fast and stable.
The proposed approach is particularly valuable for the analysis of the impact of uncertainty of the reservoir's dynamic a static parameters. This arises because the modified direct search method employed here, being convergent and independent of the initial point, ensures that the result from the multiple realisations are directly comparable because "tuning?? of the algorithm's parameters are not required in the middle of the calculation procedure.