Yang, Tao (Equinor ASA) | Arief, Ibnu Hafidz (Equinor ASA) | Niemann, Martin (Equinor ASA) | Houbiers, Marianne (Equinor ASA) | Meisingset, Knut Kristian (Equinor ASA) | Martins, Andre (Teradata) | Froelich, Laura (Teradata)
Mud gas data from drilling operations provide the very first indication of the presence of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties from mud gas data, because it would provide knowledge of the reservoir fluid properties in an early stage, continuously for all reservoir zones, and at low costs. Previous efforts reported in the literature did not lead to a reliable method for quantitative prediction of the reservoir fluid properties from mud gas data. In this paper, we propose a novel approach based on machine learning which enables us to predict gas oil ratio (GOR) from advanced mud gas (AMG) data.
The current work is based on a previous successful pilot in unconventional (shale) reservoirs. Our aim is to extend the results of the pilot study to conventional reservoirs. In general, prediction of reservoir fluid properties is more challenging for conventional reservoirs than for unconventional reservoirs, due to the complexity of petroleum systems in conventional reservoirs. Instead of building a model directly from AMG data, we trained a machine learning model using a well-established reservoir fluid database with more than 2000 PVT samples. After thorough investigation of compositional similarity between PVT samples and AMG data, we applied the model developed from PVT samples to AMG data.
The predicted GORs from AMG data were compared with GOR measurements from corresponding PVT samples to assess the accuracy of the GOR predictions. The results from 22 wells with both AMG data and corresponding PVT samples show large agreement between prediction vs. measurement. The accuracy of the predictive model is much higher than previous results reported in the literature. In addition, a Quality Check (QC) metric was developed to efficiently flag low-quality AMG data. The QC metric is vital to give confidence level for GOR prediction based on AMG data when PVT samples are not available.
The study confirms that AMG data can be used as a new data source to quantitatively predict continuous reservoir fluid properties in the drilling phase. The method can be used to optimize wireline operations and for some cases, it provides a unique opportunity to acquire reservoir fluid data when conventional fluid sampling or use of wireline tools is not possible. After high-quality PVT data becomes available in the wireline logging phase, the continuous GOR prediction can be further improved and used to determine reservoir fluid gradient and reservoir compartmentalization.
Gaol, Calvin (Clausthal University of Technology) | Wegner, Jonas (Clausthal University of Technology) | Ganzer, Leonhard (Clausthal University of Technology) | Dopffel, Nicole (BASF SE) | Koegler, Felix (Wintershall Holding GmbH) | Borovina, Ante (Wintershall Holding GmbH) | Alkan, Hakan (Wintershall Holding GmbH)
Utilisation of microorganisms as an enhanced oil recovery (EOR) method has attracted much attention in recent years because it is a low-cost and environmentally friendly technology. However, the pore-scale mechanisms involved in MEOR that contribute to an additional oil recovery are not fully understood so far. This work aims to investigate the MEOR mechanisms using microfluidic technology, among others bioplugging and changes in fluid mobilities. Further, the contribution of these mechanisms to additional oil recovery was quantified.
A novel experimental setup that enables investigation of MEOR in micromodels under elevated pressure, reservoir temperature and anaerobic and sterile conditions was developed. Initially, single-phase experiments were performed with fluids from a German high-salinity oil field selected for a potential MEOR application: Brine containing bacteria and nutrients was injected into the micromodel. During ten days of static incubation, bacterial cells and in-situ gas production were visualised and quantified by using an image processing algorithm. After that, injection of tracer particles and particle image velocimetry were performed to evaluate flow diversion in the micromodel due to bioplugging. Differential and absolute pressures were measured throughout the experiments. Further, two-phase flooding experiments were performed in oil wet and water wet micromodels to investigate the effect of in-situ microbial growth on oil recovery.
In-situ bacteria growth was observed in the micromodel for both single and two-phase flooding experiments. During the injection, cells were partly transported through the micromodel but also remained attached to the model surface. The increase in differential pressure confirmed these microscopic observations of bioplugging. Also, the resulting permeability reduction factor correlated with calculations based on the Kozeny-Carman approach using the total number of bacteria attached. The flow diversion of the tracer particles and the differences in velocity field also confirmed that bioplugging occurred in the micromodel may lead to an improved conformance control. Oil viscosity reduction due to gas dissolution as well as changes in the wettability were also identified to contribute on the incremental oil. Two-phase flow experiments in a newly designed heterogeneous micromodel showed a significant effect of bioplugging and improved the macroscopic conformance of oil displacement process.
This work gives new insights into the pore-scale mechanisms of MEOR processes in porous media. The new experimental microfluidic setup enables the investigation of these mechanisms under defined reservoir conditions, i.e., elevated pressure, reservoir temperature and anaerobic conditions.
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.
Jia, Ying (Petroleum Exploration and Production Research Institute, SINOPEC) | Shi, Yunqing (Petroleum Exploration and Production Research Institute, SINOPEC) | Huang, Lei (Research Institute of Petroleum Exploration and Development, Petrochina) | Yan, Jin (Petroleum Exploration and Production Research Institute, SINOPEC) | Sun, Lei (SouthWest Petroleum University)
The YKL condensate gas reservoir is one of the biggest condensate gas reservoirs in China and has been developed more than 10years. At present, the combination of subdivision layer, production speed optimization and horizontal well drilling has been the key to economically unlocking the vast reserves of the YKL condensate gas. The primary recovery factor, however, remains rather low due to high capillary trapping and water invasion. While primary depletion could result in low gas recovery, CO2 flooding provides a promising option for increasing the recovery factor.
The objective of this work is to verify and evaluate the effect supercritical CO2 on enhancing gas recovery and analyze the feasibility of CO2 enhance gas recovery (CO2 EGR) of condensate gas reservoir.
Firstly, novel phase behavior experimental procedures and phase equilibrium evaluation methodology for gas-condensate phase system mixed with supercritical CO2 with high temperature were presented. A unique phase behavior phenomena was also reported. Then, CO2 floodingmechanism in condensate gas reservoir was analyzed and clarified based on experiments. Finally, a series of numerical simulation work were conducted as an effective and economical means to maximize natural gas recovery with the lowest CO2 breakthrough by varying strategies, including CO2 injection rate, injection composition, andinjection timing. Meanwhile the CO2 storage volumes of different strategies were calculated.
The results show that higher gas recovery factor can be achieved with CO2 injection through appearing interphase between two fluids, maintaining reservoir pressure, driving gas like "cushion" and controlling water invasion. All strategies have moderate to significant effects on gas production. The control of injection and production ratio needs to be balanced between pressure transient and CO2 breakthrough over the producer to obtain the maximum gas production. The varying injection pressure shows a positive effect of enhancing gas production. Numerical simulation indicated that the recovery of gas reservoir was improved by around 10 percent. The total CO2 storage would be around 30-40% HCPV.
The research showed that CO2 flooding presents a technically promising method for recovering the vast condensate gas while extensively reducing greenhouse gas emissions.
Two upscaling exercises performed in 2013-14 and 2017-18 on two onshore green fields with conventional to viscous oil are presented, for which the upscaling tried to compensate the effects of grid coarsening, in particular the increase of numerical dispersion and the decrease of heterogeneity. Our methodology was to adjust the water/oil relative permeabilities called pseudo KRs in the coarse scale simulation, in order to reproduce the behavior in terms of pressure, rates, saturations and concentrations of the fine scale model, which was using microscopic rock KRs based on laboratory data.
As the upscaling depends on the fluid injected, it was done separately for waterflood and polymer flood. When done with polymer flood, the concentration of polymer had to be history matched also mainly by adjusting the Todd-Longstaff mixing parameter in addition to the KRs. As upscaling is case dependent, it was performed on several geological models, varying heterogeneity and grid size, but also rock KRs and even precocity of the polymer flood after some waterflood, to test the robustness of the approach.
It was found that pseudo-KRs for waterflood could be slightly degraded for viscous oils, whereas the upscaling was more neutral for conventional oils. This correlates well with field observation for viscous oils, where water production occurs generally a bit quicker than what numerical simulation predicts when using rock KRs, in absence of upscaling.
For polymer floods, which were considered in secondary or early tertiary mode, pseudo KRs were generally improved, mainly because the polymer steepened the saturation fronts, which can be well represented only with small lateral grid size.
The result of both upscaling exercises was that the increment of polymer flood versus waterflood was noticeably higher when computed on high resolution modelling. This is equivalent to saying that when using pseudo KRs resulting from this high resolution matching, the polymer increment on coarse grid is significantly higher than if computed without pseudo KRs. This improves the economic evaluation of the project, increasing the willingness to de-risk and implement early polymer floods on these fields.
Makwashi, Nura (Division of Chemical and Petroleum Engineering, London South Bank University) | Sarkodie, Kwame (Division of Chemical and Petroleum Engineering, London South Bank University) | Akubo, Stephen (Division of Chemical and Petroleum Engineering, London South Bank University) | Zhao, Donglin (Division of Chemical and Petroleum Engineering, London South Bank University) | Diaz, Pedro (Division of Chemical and Petroleum Engineering, London South Bank University)
Curved pipes are essential components of subsea process equipment and some part of production pipeline and riser. So far, most of the studies on of wax deposition and the possible mitigation strategies have been carried out using straight pipelines, with little attention given to curved pipes. Therefore, the objective of this study is to use an experimental flow loop designed and assembled in the lab to study and understand the mechanisms and variable parameters that affect wax depositional behaviour under the single-phase flow. Series of experiments were carried out with pipes curvatures of 0, 45 and 90-degree at different flow rates (2 and 11 L/min). The sequence in which the bends are incorporated creates non-uniformity of boundary shear, flow separation, and caused isolation of fluid around the bends that affect wax deposition, which depends on flow regimes – Reynolds number along with the radius of curvature of the bend. Prior to the flow loop experiment, the waxy crude oil was characterized by measuring the viscosity, WAT (30°C), pour point (25.5°C), n-Paraffin distribution (C10 - C67), and the saturated/aromatic/resin/asphalte (SARA) fractions
Results of this study shows that the wax deposit thickness decreases at higher flow rate within the laminar (Re<2300) and turbulent (Re>2300) flow regimes. It was observed that the deposition rate was significantly higher in curved pipes, about 8 and 10% for 45 and 90-degree, respectively in comparison to the straight pipe for all flow conditions. Increase elevation of the curved pipe, however, led to a more wax deposition trend; where a higher percentage of wax deposit was observed in 45-degree compared to 90-degree curved pipe. This trend was due addition of gravity forces to the frictional forces - influenced by the physical mechanisms of wax deposition mainly molecular diffusion, shear dispersion and gravity settling. From the results of this study, a new correlation between wax deposit thickness and pressure drop was developed. A relationship was established between wax deposit thicknesses, bend angle in pipes and wax deposition mechanisms with a reasonable agreement with published data, especially for steady state condition. Therefore, this study will enhance the understanding of the wax deposition management and improve predictions for further development of a robust mitigation strategy.
The field-scale design of chemical enhanced oil recovery (cEOR) processes requires running complex numerical models that are computationally demanding. This paper provides an efficient screening platform for the cEOR feasibility study by presenting five artificial neural network (ANN) based models. We constructed 1,100 ANN training cases using CMG-STARS to capture the variation in reservoir petrophysical properties and the range of injected chemicals properties for a five-spot pattern. The design parameters were coupled with the reservoir properties using several functional links to optimize the ANN models and improve their performances. The training cases were employed using back-propagation methods to construct one forward model (Model #1) and four inverse models. Model #1 predicts reservoir response (i.e., oil rate, water cut, injector bottomhole pressure, cumulative oil) for known reservoir characteristics (i.e., permeability, thickness, residual oil saturation, chemical adsorption) and project design parameters (i.e., pattern size, chemical slug size and concentration), Model #2 predicts reservoir characteristics by history matching the reservoir response, and Model #3 predicts project design parameters for known reservoir response and characteristics. Models #4 and #5 predict project design parameters for a targeted cumulative oil volume and project duration time, which is useful for economical evaluation before the implementation of cEOR projects.
The validation results show that the developed ANN-based models closely predict the numerical results. In addition, the models are able to reduce the computational time by four orders of magnitude, which is significant considering the complexity of cEOR modeling and the need for reliable and efficient tools in building cEOR feasibility studies. In terms of accuracy, Model #1 has a prediction error of 5% whereas the error for other four inverse ANN models is about 20–40%. To enhance the performance of the inverse ANN models, we changed the ANN structure, increased training cases, and used functional links, which slightly reduced the error. Further, we introduced a back-check loop that uses the predicted parameters from the inverse ANN models as inputs in the forward ANN model. A comparison of back-check results for the reservoir response with the numerical results delivers a relatively small error of 10%, revealing the non-uniqueness of solutions obtained from the inverse ANN models.
Lei, Zhengdong (Research Institute of Petroleum Exploration and Development, PetroChina) | Xie, Qichao (Exploration and Development Research Institute of ChangQing Oilfield Company) | Tao, Zhen (Research Institute of Petroleum Exploration and Development, PetroChina) | He, YouAn (Exploration and Development Research Institute of ChangQing Oilfield Company) | Zhu, Zhouyuan (China university of Petroleum) | Peng, Yan (China university of Petroleum) | Liu, Canhua (China university of Petroleum)
Waterflooding of fractured low permeability reservoirs are often associated with poor sweep and high water cut due to existence of natural fractures, hydraulic fractures, and artificially induced fractures. Therefore, reservoir simulation with coupled geomechanics and dynamic fractures is required for this application. In this work, we present the use of streamline-derived flux information to improve overall waterflooding performance in such complex simulation problems.
This work shows the waterflooding optimization workflow of a fractured low-permeability reservoir in ChangQing Oilfield, China. First, the finite difference simulator considering stress field and geomechanical properties is used to simulate the growth of dynamic fractures. Then, the newly formed fracture properties are included into the dual porosity/permeability reservoir simulation model. Afterwards, streamlines can be traced based on the velocity field of this model, which represent a snapshot of the inter-well fluxes. Finally, with the goal of minimizing field water production, we implement linear programming algorithms to optimize the waterflooding operation by considering the inter-well connectivity and well allocation factors.
Through reservoir simulation coupled with geomechanics, we have found that induced fracture growth rate is relatively limited at reasonable injection rate, which is also validated by field empirical observations. This can avoid fracture propagation and reduce the risk of rapid water breakthrough. We deploy our streamline tracing and linear programming based optimization program to work together with this simulation model. A controlled and cautious increase in injection rate has resulted in a positive production response in 28 producers in the pilot area. Reallocation of water to high-efficiency injectors improves sweep efficiency in the reservoir. Finally, the optimized scenario has resulted in more than 15% incremental swept volume as compared to the basic development case.
This work provides a comprehensive case study for better understanding the impact fracture growth on waterflooding performance in fractured low-permeability reservoirs. It further establishes the workflow of using streamline-based flux information for oil production optimizations in these complex simulation problems.
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.