Carbon dioxide (CO2) is considered one of the main gases that cause global warming. In this perspective, its injection in aquifers and oil and gas reservoirs has been a possible alternative to reduce its emission in the atmosphere. An alternative strategy in which CO2 is used efficiently in the Oil Industry is the Carbonated Water Injection (CWI), where the carbon dioxide is injected through the reservoir dissolved in the brine, eliminating problems of gravitational segregation and low sweeping efficiency present in other gas injection methods. Once injected, the fluid may react with the carbonate rock and inducing their dissolution, causing changes in the petrophysical properties of the rock. This work investigated changes in the average porosity of carbonate samples from Brazilian reservoir through a dynamic flow test with enriched brine with 100% CO2 injection under high pressure and high temperature conditions and simulating a region around the face of the injector well, with an injection pressure of 8,500 psi, a temperature of 70 °C and a flow rate of 2cm3/min. The core-flooding experimental setup includes two coreholders arranged in series with samples confined in its interior, which are swept by X-ray Computed Tomography (CT), taking measurements of average porosity data. The results showed that there was dissolution in the sample assembled in the first coreholder since the porosity had increased, while in the second, no significant alterations of the porosity were observed (around 8.5% of its initial value). This observation can still be confirmed by the analysis of the dissolved moles, which exhibit behavior similar to the porosity, indicating that some minerals actually suffered dissolution from the injection of carbonated brine.
Some carbonate reservoirs are known for their high CO2 content in oil. One possibility to handle this gas without environmental problems is to reinject it into the reservoir. Injection of carbonated water has been drawing attention because it is an advantageous technique when compared to gaseous CO2 injection, due to its improvement in mobility in the reservoir. The objective of this study is to evaluate the phenomenon of dissolution and precipitation during carbonated water injection in carbonate rocks. These effects are identified by analyzing the porosity variations through X-ray computer tomography images and permeability profile, determined indirectly by pressure transducers that measured the differential pressure by the fluid at the inlet and outlet of the core holders. The Coreflooding test were carried out with two core holders in series to represent a near region at the reservoir by the injection of brine saturated with 25% of CO2 in reservoir samples, composed of dolomite, calcite and clay. The test were performed using the following reservoir conditions of 8,500 psi at 70°C. Based on the experimental data provided by CT images, it can be seen that the core porosity increases or decrease during carbonated water injection due to coexistence of dissolution (increase of porosity) and precipitation (decrease of porosity) along the samples. These phenomena are observed in regions with high heterogeneity in porosity. In addition, the mineralogy of the cores is composed by three minerals, which influence in the capacity of reaction with carbonated water. For the experiment, the core placed in the core holder one presented a porosity increase and the second one decreased. On the other hand, the permeability showed a significant increase for both cores, it is believed that, the injection promoted a preferential way flow (wormhole) that affected considerably the permeability of the rock. The novelty of the investigation is that the experiments were carried out using Brazilian pre-salt carbonate reservoir rocks with mineralogy composed basically by dolomite, calcite and clay. Also, experimental work was performed at reservoir operational conditions.
During the development stage of a petroleum field, one important decision is to define the schedule for drilling the wells. Several general rules were listed for light and heavy oils. However, these rules are not always applicable and it may be important to use simulation models to test and choose the schedule. This paper consists of the development, implementation, and application of two different algorithms for optimization of wells drilling schedule. The first algorithm seeks, for each period, which well brings the best economic output. Once this well is selected, the second period of time is tested considering the remaining wells and this procedure is repeated until the last well. The second procedure is based on the reduction of search space where random schedules are generated and the best results maintained for the subsequent generation of scenarios, only allowing the wells to be drilled in the period that produced the best values of the objective function in the previous step. This procedure is repeated until each well converges to the period that results in the best economic return. Both algorithms were tested in two synthetic fields, based on the characteristics of offshore heavy oil and high average permeability reservoirs. To generate a benchmark for the solutions, a large amount of random schedules were tested and a normal distribution for net present values was generated. Both algorithms can be applied in any type of reservoirs, resulting in a very time consuming process in the cases where simulation time is very high. The results from both algorithms lead to net present values higher than at least 95% of the values from random schedules. For both cases, economic results were significantly better than those found for selecting strategy using wells ranking based in economic indicators, which is a common procedure. Both algorithms are also easy to implement and they can be inserted in a cycle of automated or assisted optimization process.
The determination of porosity and permeability distribution along the reservoir is very important and can be determined by different field and laboratory experiments, i.e., core flooding experiments, seismic and well log data, well testing. At the field level, however, information regarding spatial distribution of porosity and permeability is very sparse, and additional techniques such as geostatistics and correlations may be used. The literature presents a variety of correlations between permeability and porosity, considering different parameters, such as probability distribution functions and tortuosity of porous media. General behavior of porous media, however, can be described with a normal distribution for porosities and log-normal distribution for permeabilities. This paper proposes the use of a simplified empirical equation to represent the correlation between porosity and permeability. Methodologies to derive the empirical parameters from experimental data, or desired ranges of porosities and permeability are proposed and applied. Considerations regarding range of validity of this correlation are made by the use of a steady-state single-phase reservoir simulation. Results show that the procedures for the creation of maps of permeability, obtained from the empirical correlation, provide a reasonable distribution of values and represent well the observed data from the laboratory. The procedure for the creation of synthetic fields, obtained by fixing values of maximum and minimum permeabilities, also shows good results and can be a faster way to create synthetic field cases. Regarding the application of these correlations for upscaling, results show that the correlation remains valid when the scale is increased. Numerical dispersion can, however, be observed. The errors obtained, however, increase significantly when permeability ranges increase, meaning that the correlation can only be used with confidence when no significant variations in porosity and permeability are present. Although the literature shows other methodologies for estimating upscaling values of permeability, the approach proposed here is easier and faster to be implemented and may be used in a complementary way for field-level upscaling.
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