Enhanced oil recovery by CO2 injection is an effective method for recovering additional oil beyond water flooding. In recent years CO2-EOR has garnered considerable attention from an environmental perspective as it is considered a green-house gas. Saudi Aramco is implementing its first CO2-EOR and sequestration pilot project in a slightly depleted part of a carbonate reservoir. An important aspect of the pilot testing is the measurements of remaining oil saturation (ROS) before and after the CO2 flooding. This paper discusses a number of methods and techniques for ROS quantification before CO2 injection in the ongoing CO2-EOR pilot project. The suite of tests provide pre-CO2 injection saturations. Similar tests are planned post-CO2 injection to determine the reduction in ROS after the pilot has been completed.
Several methods have previously been used to determine ROS in oil reservoirs. In this study different logging technologies were utilized for quantification of ROS before CO2 injection to generate baseline data. The logging included resistivity and dielectric techniques. These techniques were also combined with physical formation fluid tester and sponge core analysis to determine ROS in the targeted carbonate reservoir. Finally the results are compared with a single well chemical tracer test which was conducted in the area.
This paper presents the results from various methods and explores the effect of different parameters such as lithology, porosity, salinity and water saturation on ROS quantification. The results from near wellbore techniques are compared with data from sponge core as well as the single well chemical tracer test. Methodologies of raw data processing and their interrelations are shared. This paper provides new insights into how various logging tools and coring can be optimized in the future to increase the certainty of ROS measurements.
When applying a tertiary recovery on a swept reservoir, it is very important to have a good estimate and distribution of the baseline reservoir fluid saturations after waterflooding. During secondary recovery process, a transition zone in flooded reservoir usually leaves a high level of uncertainty in term of distinguishing remaining oil saturation (ROS) versus a residual oil saturation (Sor). The reservoir heterogeneity sometimes limits the reliability of quantifying the correct amount of residual saturation that depends on core analysis and capillary pressure characteristics.
A newly emerged technique known as Digital Rock Physics demonstrates an ability to characterize properties of the porous media. This technique is based on the imaging of rock micro-structure using a micro-CT scanner. Images are segmented based on their grayscale values to extract pore network from the solid phase. Then, rock properties are estimated using extracted pore network and numerical simulations. Porosity and absolute permeability are two essential properties that can be derived from grayscale images. These properties represent storage and flow capacity of the rock.
Some rock samples, particularly carbonate rocks have complex micro-structures at several length scales. Due to limited image resolution, 3D images of carbonate rock may not have top-bottom pore connectivity. In this case, one unable to simulate fluid flow throughout the images. Therefore, permeability is computed on small image sub-volumes, where pore connectivity is revealed locally. Such approach requires long simulation runs.
In this paper, a new approach is proposed to estimate permeability from 3D carbonate rock images, where pore connectivity is not revealed from top to bottom. In this approach, first a number of texture classes that represents various textures in the 3D image are identified. For each identified texture class, several sub-volumes from the 3D image are extracted. These sub-volumes are representative of the identified textures and have local pore connectivity. To simulate fluid flow through the pore network of extracted sub-volumes Lattice Boltzmann method (LBM) is used. Permeability is then calculated using Darcy's equation. After determining permeability ranges of each textural class, the 3D image is divided into sub-volumes. Then, each sub-volume is classified into one of the specified texture classes using a modified version of the texture classification algorithm, Local Binary Pattern (LBP). In this study, traditional 2D LBP texture feature vector is adopted to handle 3D volume classification. After classification, each sub-volume is assigned a permeability value that is equivalent to its texture class. Finally, the permeability of the whole 3D image is computed by simulating Darcy's flow through the all sub-volumes.
Preliminary outcomes of the proposed technique indicate that it is able to closely estimate experimental results from the laboratory.
Oil well Inflow Performance Relationship (IPR) defines the reservoir potential to deliver fluid from reservoir into the wellbore. The IPR curve plays an important role to ensure the feasibility of drilling wells at a lower scale and the field development at a larger scale. Most of the available existing IPR correlations were developed for homogenous reservoirs. In reality, the reservoir seldom shows homogenous behavior. Using incorrect IPR correlation for a particular reservoir may induce uncertainty in the estimated flow rate for a given drawdown. This may affect the process of decision making especially in large-scale field development projects. Even though many analytical IPR correlations are available in the literature, but they are either complex or require unknown input parameters. This study focuses on the effect of composite reservoirs (more than one permeability regions/rings) behavior on IPR for solution-gas drive oil reservoirs. The main objective of this study is to develop a new empirical IPR correlation for composite reservoirs. Many investigators have developed correlations for a solutions gas drive reservoir for specific well/reservoir types such as dual permeability, multilateral, etc. where they fit well for a specific reservoir behavior and might be unrealistic for different reservoir types. The inflow performance relationships for composite reservoir with more than one reservoir properties regions (rings) are not yet investigated. Hence, there is a need to develop such correlation. The accuracy of the new IPR model is also quantified showing acceptable error as compared to other existing correlations. The new generated empirical IPR equation can be used to predict the performance of vertical wells in a solution gas drive composite reservoir with more than one heterogeneous regions (rings). This simple IPR correlation would provide petroleum engineers a simple and accurate tool for predicting the well inflow performance of composite reservoirs.
Inflow performance relationship defines the deliverability of a well. It predicts how much rate we can obtain per 1 psi of a drawdown. For under-saturated (single phase oil flow) well, the productivity index is constant and the IPR relationship is linear as long as the pressure is kept above bubble point pressure. If the reservoir pressure declines below bubble point, the IPR changes from straight line to curve as described by Vogel's formula (eq.3).
Sulfur deposition has been one of the major concerns in the sour-gas industry. This is due to the significant reduction in the deliverability of a gas well. To illustrate, in deep sour gas reservoirs, elemental sulfur often exists as a trace element in vapor at reservoir pressure and temperature. Reduction in reservoir pressure and temperature due to production of gas to the surface reduces sulfur solubility in the gas phase so that the dissolved elemental sulfur precipitates in the wellbore region of the sour gas well, thus building up sulfur scale over a period.
The compositional simulation model was GEM from CMG and we used WinProp for phase behavior of a generalized deep sour gas well in the Middle East.
We observed that the deposition of sulfur is in the tubing and not like salt/scale deposition in the casing which is due to evaporation and super saturation in the brine phase as it produced through the perforations.
Sour gas reservoirs are those reservoirs with high content of Hydrogen Sulfide (H2S) and/or elemental sulfur. These reservoirs are widely distributed around the globe. In this case, of deep sour gas reservoirs, sulfur is present in trace amounts and is dissolved within the hydrocarbon gas phase at reservoir pressure and temperature. However, sulfur gas solubility decreases with a reduction in pressure, therefore, sulfur will deposit around the well bore (Kennedy and Wieland 1960). Therefore, the sulfur solubility in the gas phase decreases below its thermodynamic saturation point due to the reduction in pressure and temperature and, hence, sulfur deposition is induced. This deposition can occur in the reservoir, wellbore and in the surface facilities (Hands et al. 2002; Shadid and Zekri 2006). Moreover, solid sulfur deposition becomes critical when the deposition occurs near the well-bore region. This causes a significant reduction in the inflow performance of the sour-gas wells. Mahmoud (2014) also stated that the inflow performance of the sour-gas well can be significantly reduced due to the deposition of elemental sulfur within the formation mainly in the near-wellbore region.
Previous approaches to downhole flow allocation have used traditional nodal analysis software. This paper provides practical experience developing a solution for zonal flow allocation using an advanced completion and near-wellbore (NWB) hydraulics simulator. This solution was implemented in a green field development in the Middle East where three oil-producing wells completed with an intelligent well completion (IWC) system commingle production from multiple reservoirs. These smart wells were installed with interval control valves (ICVs) to control the commingled flow and permanent downhole gauges (PDHGs) to provide real-time pressure and temperature (P/T) data that were used in flow allocation.
IWCs plays a key role in improving hydrocarbon recovery by providing operating companies the ability to selectively and remotely monitor, control, and optimize production from or injection to multiple zones, laterals, formation layers, or reservoirs. Applications of zonal monitoring and control in multizone completion include limiting production of unwanted fluid from a specific zone, preventing crossflow between reservoirs, selective testing or stimulating of each lateral, limiting drawdown in sand-prone formations, balancing zonal injection, and optimizing zonal production to depletion plan objectives. IWCs have been adopted by several operators worldwide since 2000. Several field cases are published by operators highlighting the key role of IWCs in managing reservoirs that resulted in increased recovery (Van Den Berg et al. 2010).
The three key elements of an IWC system are downhole flow control, downhole sensors, and feedthrough packers. Downhole flow control, also referred to as ICVs, has multiple choke positions for controlling production from or injection to a reservoir. Depending on the depletion strategy and zonal production requirement, an ICV choke setting can either be increased or decreased remotely from surface by means of control lines. Downhole sensors, also referred to as PDHGs, are used to measure P/T inside the tubing or annulus under both static and flowing conditions. PDHGs are useful for monitoring the well and zonal responses for a given operating condition. Optimizing the well performance requires continuous analysis of PDHG data together with other dynamic well performance parameters. Multifeedthrough packers for zonal isolation can be either hydraulically set or swellable feedthrough packers.
In matrix acidizing, the aim is to create long conduits (wormholes) inside the reservoir formation which ultimately results in productivity increase. Acid in oil emulsion is used in the industry for stimulating carbonates with diesel commonly as the oil phase and hydrochloric acid (HCl) as the acid phase. Emulsifying HCl has numerous benefits over regular HCl. Perhaps the main benefit is deep penetration near the wellbore. Also, less corrosion damages are caused since the external phase is hydrocarbon (diesel). Several studies showed the success of replacing diesel as an external phase with other hydrocarbon oil, such as crude oil and xylene.
This work utilizes the extra hydrocarbon left unused –or sometimes dumped– from refineries, referred to as waste oil. The chemical composition of waste oil is studied. The HCl-waste-oil emulsion is prepared using 15 wt% HCl with a ratio of 70:30 of acid-to-oil. This paper reports results on the thermal stability and rheological properties of the HCl-waste-oil emulsion. All thermal stability experiments are conducted at a high temperature, 120 °C.
The results show that the HCl-waste-oil emulsion is a shear-thinning fluid. Power-law model is applicable seamlessly to all of the apparent viscosity data for all measured temperatures. The optimum conditions are found to be; 0.5vol% and 600 rpm for emulsifier concentration and mixing speed, respectively. Overall, the lab results show a promising potential for the HCl-waste-oil emulsion to be used in the field.
This work takes into account; reducing the budget of acidizing job along with environmental concerns. Apart from using low emulsifier concentration and low mixing speed, it makes use of the unwanted hydrocarbon from refineries.
An emulsion is a combination of two immiscible liquids: oil and water. The emulsion is prepared using a mechanical and/or a chemical means to reduce the interfacial tension between the two immiscible liquids. Mechanical means such as providing enough agitation using a blender. Chemical means such as adding special surfactants. In both scenarios the interfacial tension is reduced resulting in an emulsion. Since the emulsion is thermodynamically unstable it is bound to separate into its parent liquids. Hence, stability of the emulsion is of critical importance for well stimulation applications. Obviously, combining the mechanical and chemical means will result in a more stable emulsion. In oil and gas industry, emulsions are widely used to stimulate wells in order to increase the productivity or injectivity. Emulsions are used with acid as the water phase and diesel as the oil one. For carbonate reservoirs, diluted HCl acid is the water phase; hence, referred to as emulsified acid.
Kuwait Oil Company conducted a geophysical surveillance program to optimize development options in a shallow heavy oil field in Kuwait. Two optimized 3D Vertical Seismic Profiles (3DVSPs) were acquired in January 2016 to help understand the effectiveness of this EOR project. Goals of this project included acquiring repeatable baseline surveys for 4DVSP surveys, attaining high resolution 3DVSP data, imaging the sealing cap rock shale and two thin vertically stacked reservoirs, and estimating the steam chamber size just after a 30-day steam injection cycle.
One major problem with recording shallow VSP data is the possibility of spatial aliasing due to the slow propagation velocities of P and S waves affecting the ability to achieve desired frequency range. Therefore extensive pre-survey modeling was required in order to determine the optimum source-receiver configuration. The team decided on innovative survey parameters purposely designed to obtain higher frequencies than previously attained in this area to improve the vertical and spatial resolution sufficient to achieve the project goals listed above. The resulting two 3DVSP datasets were then processed and imaged using a patented vector pre-stack Kirchhoff depth migration. Inversion work and qualitative interpretation were then applied to both data volumes to help achieve all the desired goals.
Extensive planning and flawless execution of the two-well 3DVSP operation resulted in the completion of both survey acquisitions in a total of 13 days without incurring any QHSE incidents and having 100% operating efficiency. Frequencies obtained in these surveys were more than 30% higher than previously achieved in this same area. These high frequencies resulted in vertical resolution sufficient to image the sealing shale layer and both of the steam injected reservoir sands as well as the necessary spatial resolution to image a small steam chamber. The novel modelling, acquisition and processing/interpretation methodology described have demonstrated that accurate subsurface imaging in this environment is achievable. The results have contributed to and altered the steam flood expectations and will provide key information that would not otherwise have been available to develop the best development options. Additional 3D and 4DVSPs are currently being acquired.
Extensive modeling enabled innovative customization of an innovative acquisition design, optimized acquisition operations, parallel processing, and interpretation techniques have allowed for a time efficient acquisition-to-results turnaround.
Carbon Dioxide (CO2) injection is considered one of the most widely used enhanced oil recovery (EOR) methods due to CO2 availability, applicability. Contributing to its popularity is the ability to perform carbon capturing and storage alongside EOR in which CO2 is stored in reservoirs to mitigate global warming potential. Experiments have been performed to measure oil recovery factor, CO2 storage efficiency, and co-optimization function of a CO2 flood in horizontal cores but none has studied the effect of gravity on all three.
This paper presents horizontal and vertical CO2 flooding experiments to quantify the gravity effect on oil recovery and CO2 storage. Irreducible water saturation of 27% represents the initial condition for both experiments. A homogeneous Bentheimer sandstone core is used while a mixture of hexane (65%) and decane (35%) represents the oil phase. The Oil recovery, pressure drop and effluent compositions are recorded during the experiment.
It was found that vertical flood exhibited high displacement efficiency but low volumetric sweep efficiency and by eliminating the effect of gravity, not only oil recovery increases, but also CO2 storage efficiency. In the vertical flood, oil recovery, CO2 storage efficiency, and the co-optimization function increase by 24%, 7%, and 15%, respectively, compared to horizontal flood. The stabilized displacement front delays breakthrough and effectively improves oil recovery and storage efficiency.
CO2 injection is one of the most popular EOR methods worldwide. If only the depth and oil gravity of reservoirs are considered as screening criteria, over 80% of worldwide reservoirs would qualify for CO2 injection (Lake, 1989; Taber et al., 1997). CO2 has been widely used as a solvent to improve oil recovery due to its relatively wide availability and documented performance. CO2 displacement efficiency is more than other solvents such as methane and nitrogen due to its relatively higher viscosity (about 2 – 3 times higher) resulting in lower CO2 – crude oil mobility ratio (Lake, 1989; Taber et al., 1997). This favorable property helps CO2 become a primary target solvent for EOR. Yet, there is much more to CO2 injection than just oil recovery, geological storage of CO2 has recently become an important aspect of CO2 EOR.
During history matching of observed production data of brown fields, one of the key matching parameters is the water break-through time. Water break-through time is the time at which significant water production begins at a producing well. During the simulation of an immiscible displacement process, numerical dipersion is a well known undesirable simulation artifact which makes water flood-front to move faster when the simulation grid-blocks are coarser. In this paper, we present an approach to reduce numerical dispersion and ensure that the simulated flood-front movement is similar, whether we use coarse grid-blocks or fine grid-blocks in simulation.
The approach is based on the correction of laboratory relative permeability data, using the shock front water saturation (Swbt) obtained from fractional flow curve. Swbt is the water saturation at the contact point between a tangent drawn from the connate water saturation (Swi) to the fractional flow curve. Once we obtain Swbt, we then set the critical water saturation of the water relative permeability curve to Swbt.
We created different scenarios of grid block sizes and simulated a steady state water injection process using the corrected water relative permeability curve. We based our study conclusions on results from both line drive and 5-spot water injection patterns.
The result showed six (6) months difference in predicted water break-through dates when we used the laboratory relative permeability data as is, but with this new approach, the various scenarios of grid block sizes showed similar water break-through dates. This new methodology effectively eliminates the impact of simulation grid size on water break-through prediction results. During geo-model construction, we do not know in advance what impact our chosen grid size would have on flow dynamics, and once the geo-modeling is finalized it could be time consuming to re-do the gridding and layering of the geo-model. We also take note that many times we are constrained to build simulation models with large grid-sizes because of computational limitations, especially in large reservoirs. The new approach presented in this paper would ensure that any size of grid-block used in simulation, would predict similar flood-front movement and hence similar water break-through time as fine grid simulation.
Our approach helps to ensure better reliability of simulation results in cases where computational limitations or large size of reservoir makes it necessary to build coarse grid simulation models.
The determination of optimum well locations and number of wells needed during green field development always comes with unprecedented challenges because of the geological uncertainty, and the non-linear relationship between the input and output variables associated with real reservoirs. These variables are key sources affecting the viability and validity of the results.
Reservoir simulation is one of the least uncertain and most reliable prediction tools for dynamic performance of any reservoir. As field development progresses, more information becomes available, enabling us to continually update and, if needed, correct the reservoir description. The simulator can then be used to perform a variety of exercises or scenarios, with the goal of optimizing field development and operation strategies. Optimizing well numbers or locations under such geological uncertainty is achieved by using a reservoir simulator under several geological realizations, and these require multiple reservoir simulations to estimate the field performance for a given well configuration at a given location.
Using reservoir simulation becomes impractical when dealing with real field cases incorporating multimillion cells because of the associated CPU demand constraints (Bouzarkouna et al., 2012). For instance, to determine the optimum well locations in a giant field that will result in the most efficient production rate scenario, one requires a large number of simulation runs for different realizations and well configurations. A large amount of runs is technically difficult to achieve even if we have access to super computers.
The Fast Marching Method (FMM), which is based on solution of Eikonal equation, can be used to find the optimum well locations in a green oil field by tracking the pressure distribution in the reservoir. The FMM will enable us to calculate the radius of investigation or pressure front as a function of time without running any simulation and with a high degree of accuracy under primary depletion conditions.
The main purpose of this paper is to study the effect of mobility on FMM and extend the investigation of its validity to include two phase-flow and convection-dominated flow and evaluate the ability of the methodology to predict the dynamic performance of the reservoir during pseudo-steady state flow regime.