Pre-salt Carbonate Reservoirs Research Articles

The influence of major faults and fractures on the development of non-matrix porosity system in a pre-salt carbonate reservoir, Santos Basin – Brazil

Faults and fractures are central for characterizing the permeability distribution in carbonate reservoirs since they act as pathways for diagenetic fluids that often favor intense rock dissolution and permeability. Usually, high permeability zones and fractures are not easily recognized in seismic data due to limited resolution and they are often associated with higher concentrations of hydrocarbons or even significant fluid losses during drilling, thus creating a challenge for hydrocarbon exploration. In the Santos Basin, southeast Brazil, the pre-salt carbonate reservoirs from the Barra Velha Formation (BVE) are the main hydrocarbon producers in Brazilian Atlantic margin and well-known for being extremely heterogeneous, exhibiting complex dual-porosity systems. In this study, we built a conceptual model of these fracture zones and non-matrix porosity formation that helped narrowing the understanding of these complex systems. The characterization of faults and fractures was carried out using seismic, well-logs, and borehole image data to understand the influence of these structures in the porosity formation along the Barra Velha Formation. In the study area, three fault sets were defined (F1, F2, and F3) from seismic data. F1 represents to the larger faults, while the F3 fault set represents the smaller faults related to the reactivation of F1; both sets being oriented NE-SW. The F2 fault set is associated with the rift formation and is oriented to NNE-SSW. These three fault sets compartmentalized the studied area into different domains, each exhibiting distinct fracture sets. The natural open fractures were formed during the reactivation of rift faults and are oriented mainly NW, NNE-NNW, NE, and ENE and were identified across the entire study area, but with different intensity values. The fracture intensity closely relates to the distance from major faults where the wells with the highest fracture intensity occurs located 150–590 m from the larger F1 fault set. Scan-lines were conducted throughout the area to determine the fault width, and an average value of 1.2 km was established. Seven non-matrix porosity classes were characterized and classified into stratigraphically concordant and discordant non-matrix pore types at well scale through borehole image interpretation. The Barra Velha Formation exhibit higher occurrence of stratigraphically discordant non-matrix porosity related to fractured zones while stratigraphically concordant non-matrix porosity is mainly controlled by the paleotopography of the study area. Overall, non-matrix porosity formation tends to follow an orientation that suggests a preferential dissolution flow towards NE and ENE directions. Intervals with higher silica content shows a positive correlation with both fracture intensity and stratigraphically discordant non-matrix porosities. This work provides a conceptual model about the fractures and non-matrix porosity distribution in pre-salt carbonate rocks that can help address some of associated structural and stratigraphic uncertainties during field appraisal and development.

Seismic quantitative interpretation of diagenetic processes: A study in Brazilian pre-salt carbonate reservoirs

The Brazilian pre-salt carbonate province is a scientific frontier that has been subject of extensive research and academic discussion. Santos basin carbonates show that reservoir quality is strongly conditioned by the characteristics of the depositional environment and its associated diagenetic history and alterations. Dolomitization and silicification are two of the most common diagenetic processes in Brazilian carbonates, and the combination of sedimentary and diagenetic complexity leads to a much more heterogeneous reservoir, especially complicated for geoscientists trying to mimic these geological features in terms of static and dynamic modelling. This study proposes a methodology for seismic derived diagenetic properties calculation through seismic quantitative interpretation and classification of inverted P- and S-impedance volumes applied to Brazilian Pre-Salt carbonate reservoirs. Our proposition is to establish relations between petroelastic properties and diagenetic features, first in the well-log domain and, later, in the seismic domain through different quantitative probabilistic techniques. Using the available seismic data and probabilistic approaches through stochastic inversion and Bayesian facies classification, we can interpret the occurrence of diagenetic silica and dolomite in 3D volumes. The volumetric analysis generated through the presented methodology can provide much more insights into the sedimentary history of the field, especially for static and dynamic porosity and permeability modelling.

Enhancing permeability estimation methods in Brazilian pre-salt complex carbonate reservoirs

Carbonate pre-salt reservoirs pose formidable challenges for formation evaluation and estimation of petrophysical properties such as rock flow capacity. The high complexity of the pore system and its textural heterogeneity often lead to poor predictions when using conventional formation evaluation methods. This paper discusses and tests the applicability of two approaches to calculate the absolute permeability curves for the carbonate reservoirs of the Barra Velha Formation in the Santos Basin, proposing a fine-tuned workflow for these complex rocks. In developing our workflow, we used data from a case study well, comprising a complete well log suite and two formation tests, and routine core analysis results (RCAL) in core plugs and sidewall cores. Our workflow consists of: (1) reinterpreting the nuclear magnetic resonance (NMR) log in vugular intervals by decomposing the transversal relaxation time spectra; (2) calculating the absolute permeability by the Timur–Coates model and adjusting the coefficients with the RCAL results from representative samples; (3) applying the Flow Zone Indicator (FZI) method for rock typing to optimally define Hydraulic Flow Units (HFU); (4) checking the consistency of HFUs regarding pore geometry and lithological characteristics; (5) evaluating the performance of the models against core data and formation tests. The predicted permeability curves performed well for the NMR and FZI models when compared to the RCAL data from representative samples, with mean absolute errors for the logarithm of permeabilities equal to 0.78 and 0.87, respectively. This represents an improvement of 15% and 5% when compared to the simplistic approach that uses a power law to relate porosity to permeability from RCAL. These curves also reasonably reproduce the results from the formation tests for the top part of the reservoir, where matrix porosity dominates the flow. However, the NMR and FZI permeability curves underestimate the test results at the bottom part of the reservoir, where karstic and fracture features dominate, demonstrating limitations in these permeability estimation methods for this specific scenario. From our observations, we propose several improvements to enhance the current methods for estimating absolute permeability in pre-salt carbonate reservoirs. In the case of the NMR approach, it is essential to consider the effects of mud invasion in vugs for the correct estimation of the proportions of free and irreducible fluids. In the FZI approach, optimization in defining the quantity and limits of hydraulic flow units is important, which shows that four units are sufficient to represent the reservoir interval.

Unraveling the hidden relationships between seismic multiattributes, well-dynamic data, and Brazilian pre-salt carbonate reservoirs productivity: A shallow versus deep machine-learning approach

During the initial phases of an E&P project, the most reliable data on the reservoir’s deliverability are acquired via drill stem tests (DST), which provide the productivity per flow unit whenever production logging tool data are available. However, DSTs are restricted to a few kilometers, whereas seismic data cover large areas. The integration of these data has been challenging, particularly due to the difference in scale between them. So, a new workflow to determine the relationship between poststack seismic attributes and reservoir productivity using classic supervised (shallow) and deep-learning regression algorithms was developed. The DST parameters were predicted over the entire seismic cube, which can be extremely valuable for the decision-making process. The data set is from the Brazilian deep-water presalt carbonate reservoirs of the Mero Field, which is a well-explored area with a plethora of test and production data. It is adjacent to an underexplored Central Libra appraisal plan area, which is covered by the same seismic survey. Thus, any relationships between seismic attributes and well productivity data observed at the Mero Field are extrapolated to the adjacent underexplored area. Ten seismic attributes and DST data from 10 wells of the Mero Field were used to train shallow and deep-learning supervised regression algorithms for the prediction of flow capacity and productivity index seismic cubes. Twenty development wells (blind tests) were used for the assessment of our predictive models. The highest percentage of correct predictions at the blind test wells (85%) was obtained with random forest regression using six attributes derived from a spectrally balanced full-stack volume, and neither amplitude-variation-with-offset nor inversion data were needed. Deep learning provided lower performance (75%) at a higher computational cost. It demonstrated a new reservoir derisking tool that can be used for project optimization in areas covered by the same seismic survey.

Benefits of Integrating Seismic and Gravity Data in a Subsalt Environment. A Case Study at Block BM-C-33, Deepwater Campos Basin, offshore Brazil

Imaging subsalt layers is challenging in the BM-C-33 block in the Campos Basin's ultradeep waters. This block is important as it has three significant gas and condensate discoveries in the pre-salt carbonate and volcanic reservoirs -- Seat, G൥a, and P⭠de A洣ar. Understanding basement morphology is essential to better define the petroleum system in the area. To that end, we performed a 2D gravity modeling exercise along a northwest-southeast section, using seismic interpretation as input to reduce the ambiguity of the modeling exercise. To achieve this, we fixed the main sedimentary horizons and their densities (calculated via well-log information) to better estimate the top of the basement morphology. This interpretation strategy better delineated the pre-salt sedimentary section and the complex structural framework with two asymmetric grabens bounded by a prominent horst, interpreted as a migration focusing high in the BM-C-33 area. In addition, our findings show that obtaining clear images remains challenging even after extensive processing of the seismic data set. We suggest that seismic node acquisition with ultra-long offsets and multi-azimuthal illumination and then carefully processing the data is required to accurately reveal the area's pre-rift section and basement morphology under study.

Sedimentary build-ups of pre-salt isolated carbonate platforms and formation of deep-water giant oil fields in Santos Basin, Brazil

In response to the problems of unclear distribution of deep-water pre-salt carbonate reservoirs and formation conditions of large oil fields in the Santos passive continental margin basin, based on comprehensive utilization of geological, seismic, and core data, and reconstruction of Early Cretaceous prototype basin and lithofacies paleogeography, it is proposed for the first time that the construction of pre-salt carbonate build-ups was controlled by two types of isolated platforms: inter-depression fault-uplift and intra-depression fault-high. The inter-depression fault-uplift isolated platforms are distributed on the present-day pre-salt uplifted zones between depressions, and are built on half- and fault-horst blocks that were inherited and developed in the early intra-continental and inter-continental rift stages. The late intra-continental rift coquinas of the ITP Formation and the early inter-continental rift microbial limestones of the BVE Formation are continuously constructed; intra-depression fault-high isolated platforms are distributed in the current pre-salt depression zones, built on the uplifted zones formed by volcanic rock build-ups in the early prototype stage of intra-continental rifts, and only the BVE microbial limestones are developed. Both types of limestones formed into mound-shoal bodies, that have the characteristics of large reservoir thickness and good physical properties. Based on the dissection of large pre-salt oil fields discovered in the Santos Basin, it has been found that both types of platforms could form large-scale combined structural-stratigraphic traps, surrounded by high-quality lacustrine and lagoon source rocks at the periphery, and efficiently sealed by thick high-quality evaporite rocks above, forming the optimal combination of source, reservoir and cap in the form of “lower generation, middle storage, and upper cap”, with a high degree of oil and gas enrichment. It has been found that the large oil fields are all bottom water massive oil fields with a unified pressure system, and they are all filled to the spill-point. The future exploration is recommended to focus on the inter-depression fault-uplift isolated platforms in the western uplift zone and the southern section of eastern uplift zones, as well as intra-depression fault-high isolated platforms in the central depression zone. The result not only provides an important basis for the advanced selection of potential play fairways, bidding of new blocks, and deployment of awarded exploration blocks in the Santos Basin, but also provides a reference for the global selection of deep-water exploration blocks in passive continental margin basins.

Integration between experimental investigation and numerical simulation of alkaline surfactant foam flooding in carbonate reservoirs

In Brazil, pre-salt carbonate reservoirs are largely responsible for the current increase in oil production. However, due to its peculiar characteristics, increasing oil recovery by water injection is not enough. Therefore, we seek to evaluate the recovery potential using chemical methods (cEOR). Among these, the Alkali Surfactant Foam (ASF) method appears with high potential, a variant of Alkali Surfactant Polymers (ASP) without the problems presented by it. Therefore, this work presents an innovative methodology, which seeks to evaluate the potential for recovery with ASF in carbonate reservoirs by integrating experimental characterization and recovery prediction using reservoir simulation. For this, phase behavior and adsorption analyses were carried out. The experimental results provided key parameters for the simulation, such as optimal salinity, surfactant adsorption, foam mobility reduction factors. The results are from two case studies of AS and ASF flooding, using a section of UNISIM-II benchmark, using a one-quarter of five-spot model. Having the modelling for these cEOR methods defined, an optimization process for each method was applied, allowing a reliable comparison among the methods and over a base case of water injection, seeking the maximization of the net present value (NPV). As a result, in the experimental part, a low interfacial tension (IFT) value of 0.003 mN/m was achieved with a surfactant adsorption reduction of 17.9% for an optimal setting among brine (NaCl), alkali (NaBO2.4H2O), and surfactant (BIO-TERGE AS 40). In the reservoir simulation part, using a fast genetic algorithm in the optimization process, a NPV of US$ 14.43 million higher than the base case (water injection) and a 4.5% increase in cumulative oil production for the ASF injection case were obtained. Considering the analyses of production curves (cumulative oil production and oil rate) and oil saturation maps, a considerable oil production anticipation was observed, which was the main reason for NPV improvement, proving the high potential for application of the ASF method in carbonate reservoirs.

Geological Insights from Porosity Analysis for Sustainable Development of Santos Basin’s Presalt Carbonate Reservoir

Geological Insights from Porosity Analysis for Sustainable Development of Santos Basin’s Presalt Carbonate Reservoir

Correlation between geomechanical and sedimentary facies and their implications for flow unit definition in the pre-salt carbonate reservoir, Brazil

Carbonate reservoirs are of great economic importance due to their frequent association with high permeability and hydrocarbon storage capacity. One of the most significant discoveries of this type of reservoir in recent decades has been the Brazilian Pre-salt. This deep reservoir has unusual depositional features, consisting of a wide variety of textures with different compositions, influenced by diagenetic overprinting that modify most of its mechanical, elastic and petrophysical properties. Despite the marked heterogeneity, these carbonates are characterized by excellent reservoir quality. The objective of this study is to establish a correlation between geomechanical behavior and sedimentary facies and its implications for the definition of flow units in the Barra Velha Formation, the main reservoir of the Brazilian Pre-salt. Thus, using a database from the Buzios field composed of well logs (conventional and advanced), well tests, thin sections, and laboratory petrophysics, geomechanical facies (GMFs) were defined using dynamic geomechanical modeling and an unsupervised algorithm (K-mean clutering), followed by textural classification of sedimentary facies and definition of flow units (FUs) on the decametric scale. These classifications were compared using frequency histograms. The geomechanical model revealed that the in-situ stress state exhibits a dual regime, between normal and strike slip. In addition, it was found that the direction of the maximum horizontal stress is in the NE-SW azimuth. In this context, four geomechanical facies were defined, which showed a notorious variation in mechanical strength. The strongest GMFs consisted mainly of well-cemented Grainstones and Packstones with no apparent porosity or microcrystalline porosity and correlated with the FU with the worst production rates. On the other hand, the weaker GMFs were mainly composed of Grainstones and Spherulistones with high intergranular porosity generated by dissolution processes, with higher risk of pore collapse and correlated with the FUs with the best production rates. However, this classification also identified laminated mudstones with microporosities associated with FUs that act as flow barriers. Geomechanical facies have also been incorporated into reservoir development by evaluating wellbore stability, fault reactivation risk, and brittleness index for future CO2 injection projects.

Formation mechanical mechanism of low-angle fractures in pre-salt carbonate reservoirs: a case study from Carboniferous KT-I formation of the NT oilfield in the eastern margin of the Precaspian Basin, Kazakhstan

Fracture is an important factor that affects the oil and gas productivity of carbonate reservoirs. Much researches have been done on the origin of high-angle fractures in carbonate reservoirs, but few efforts have been made on the genetic mechanical mechanism of low-angle fractures. Based on the seismic data, core data, conventional logging data and rock mechanics experimental data, combined with three-dimensional in situ stress field simulation methods, the features, formation geological conditions and genetic mechanical mechanism of low-angle fractures (LAFs) were analyzed by applying Coulomb–Moore criterion, Griffith criterion and non-coordination criterion. The proportion of the number of shear fractures is as high as 90.2%, while that of tensile fractures is only 9.8% in the study area. Shear fractures are mainly unfilled fractures, and tensile fractures are mainly partially filled fractures. The LAFs were formed in the second tectonic movement, in which the knee-fold structure with high in the west and low in the east developed in the study area. The buried depth of most parts of the KT-I formation is 800 m when the study area develops the knee-fold structure, with a maximum depth of 1800 m and a minimum buried depth of 70 m, and the dip angle of the steepest part of the stratum is about 20°. A large number of LAFs were formed in the study area under the joint influence of tectonics and abnormally high pressure of water, including near-horizontal LAFs in the non-weak fabrics section (type I low-angle shear fractures), the LAFs having a certain angle with bedding in the non-weak fabrics section (type II low-angle shear fractures) and near-horizontal LAFs in the weak fabrics section (type III low-angle shear fractures). The formation of type I and type II low-angle shear fractures follows the Coulomb–Moore criterion. Type I low-angle shear fractures are formed in strata with a certain dip angle, while type II low-angle shear fractures are formed in near-horizontal strata. Type III low-angle shear fractures are formed under the comprehensive influence of pre-existing weak fabrics and strong horizontal extrusion, which follows the non-coordination criterion. Low-angle tensile fractures are mainly caused by abnormally high pressure and reverse faults in the study area, following Griffith’s criterion. The research in this paper not only reveals the formation mechanical mechanism of LAFs in pre-salt carbonate reservoirs but also provides guidance for the prediction of LAFs and solving the problem of water channeling caused by LAFs in oil fields.

Geostatistical seismic inversion and 3D modelling of metric flow units, porosity and permeability in Brazilian presalt reservoir

Flow units (FU) rock typing is a common technique for characterizing reservoir flow behavior, producing reliable porosity and permeability estimation even in complex geological settings. However, the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study. This paper proposes a workflow to generate numerous possible 3D volumes of flow units, porosity and permeability below the seismic resolution limit, respecting the available seismic data at larger scales. The methodology is used in the Mero Field, a Brazilian presalt carbonate reservoir located in the Santos Basin, who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history. We generated metric flow units using the conventional core analysis and transposed to the well log data. Then, given a Markov chain Monte Carlo algorithm, the seismic data and the well log statistics, we simulated acoustic impedance, decametric flow units (DFU), metric flow units (MFU), porosity and permeability volumes in the metric scale. The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios, without losing the seismic lateral control. In other words, every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area, even in the metric scale. The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

The impact of heterogeneity and pore network characteristics on single and multi-phase fluid propagation in complex porous media: An X-ray computed tomography study

This study investigates the impact of pore network characteristics on fluid flow through complex and heterogeneous porous media, providing insights into the factors affecting fluid propagation in such systems. Specifically, high-resolution or micro X-ray computed tomography (CT) imaging techniques were utilized to examine outcrop stromatolite samples of the Lagoa Salgada, considered flow analogous to the Brazilian Pre-salt carbonate reservoirs. The petrophysical results comprised two distinct stromatolite depositional facies, the columnar and the fine-grained facies. By generating pore network model (PNM), the study quantified the relationship between key features of the porous system, including pore and throat radius, throat length, coordination number, shape factor, and pore volume. The study found that the less dense pore network of the columnar sample is typically characterized by larger pores and wider and longer throats but with a weaker connection of throats to pores. Both facies exhibited less variability in the radius of the pores and throats in comparison to throat length. Additionally, a series of core flooding experiments coupled with medical CT scanning was designed and conducted in the plug samples to assess flow propagation and saturation fields. The study revealed that the heterogeneity and presence of disconnected or dead-end pores significantly impacted the flow patterns and saturation. Two-phase flow patterns and oil saturation distribution reveal a preferential and heterogeneous displacement that mainly swept displaced fluid in some regions of plugs and bypassed it in others. The relation between saturation profiles, porosity profiles, and the number of fluid flow patterns for the samples was evident. Only for the columnar plug sample was the enhancement in recovery factor after shifting to lower salinity water injection (SB) observed.

An integrated 3D digital model of stratigraphy, petrophysics and karstified fracture network for the Cristal Cave, NE-Brazil

Digital Outcrop Models (DOMs) are virtual representations of geological features. Although DOMs are widely used tools in geosciences, their integration with other datasets remains relatively underexplored. We combined a DOM, derived from a photogrammetric survey of a carbonate sequence, with lithostratigraphic, petrophysical (porosity, permeability and uniaxial compressive strength), fracture distribution, and karst dissolution information to compose a single integrated three-dimensional digital model. The study site is one of the entrances of the Cristal Cave (São Francisco Craton, Northeastern Brazil), which has been used as a structural and diagenetic outcrop analog for the Brazilian pre-salt carbonate reservoirs. Data from fracture distributions, measured on the exposed surfaces of the cave, were used to build a Discrete Fracture Network, based on the solution of the stereology inverse problem. Fracture apertures were then modified to generate different scenarios of karstification, thus composing Discrete Fracture and Karst Networks. This integrative approach brought relevant insights into the cave development due to dissolution along fracture clusters. Our methodology offers better geological data handling to build static models to be used in a fluid flow modeling environment, contributing to bridge the gap between geophysics/geology and engineering approaches.

Utilizing integrated artificial intelligence for characterizing mineralogy and facies in a pre-salt carbonate reservoir, Santos Basin, Brazil, using cores, wireline logs, and multi-mineral petrophysical evaluation

In complex carbonate reservoirs, it is crucial to understand the connections between reservoir compositions (minerals, facies, and properties). Conventionally, core samples have been used to measure reservoir parameters and identify minerals and facies. However, core samples are limited to certain wells. Therefore, additional techniques are necessary to overcome this limitation comprehensively. This study aims to identify key mineralogical and facies components of the Barra Velha Formation (BVF) and their relation to reservoir parameters. Dolomite, calcite, quartz, and clay minerals were commonly found using X-ray Diffraction (XRD). By employing multi-mineral (MM) petrophysical evaluations, we accurately recreated mineral quantities from XRD and petrophysical properties from core analysis to ensure reliability. Replications of inputs well logs and the mineralogical volume from spectroscopic (ECS) were used as reliability techniques for validating the MM. A total of 47 wells were analyzed using those methods. In this study, the classification of facies was accomplished through the selection of three prominent supervised artificial intelligence techniques, among which SOM, a widely employed method for facies estimation, was included. Additionally, the ensemble methods of Random Forest and XGBoost were adopted due to their recognized efficacy in handling tabular data and their track record of success in machine learning and artificial intelligence competitions. Remarkably, the performance evaluation revealed that Random Forest and XGBoost algorithms outperformed SOM, yielding the most favorable outcomes in this context. An integrated analysis of mineralogical and facies results was conducted, incorporating production data and special profiles such as nuclear magnetic resonance (NMR) and Wellbore Image (WBI) to identify vug-containing areas. The dolomitic facies exhibited favorable reservoir qualities, influenced by diagenetic processes represented by vuggy porosity, which enhanced permeability. Shrubstones, spherulites, and reworked facies showed superior petrophysical qualities and were connected with productive regions, leading to elevated dolomite concentrations, and vuggy abundance. The study highlights two major innovations: the use of mineralogical volume from multi-mineral assessments as inputs for AI-based property estimation to improve facies estimates, and the discovery of relationships between facies, minerals, and reservoir properties, compared to production data. This understanding allows for more accurate static model creation, optimal production interval selection, improved hydrocarbon recovery, and better specification of stimulation processes.

Digital Rock Analysis Based on X-ray Computed Tomography of a Complex Pre-salt Carbonate Reservoir from the Santos Basin, SE Brazil

Digital Rock Analysis Based on X-ray Computed Tomography of a Complex Pre-salt Carbonate Reservoir from the Santos Basin, SE Brazil

Application of unsupervised learning and deep learning for rock type prediction and petrophysical characterization using multi-scale data

This study integrates well log data, routine core analyses, microcomputed X-ray tomography (μCT) images, and sedimentary petrography to accurately characterize and evaluate the carbonate reservoirs of the Barra Velha formation (Aptian) of the Santos Basin within Brazilian pre-salt region. In these carbonate reservoirs, the porous system is extremely diverse and variable, making it challenging to establish rock typing with comparable petrophysical properties. Based on this integrated study, the reservoir sequences were characterized and a precise definition of four reservoir rock types (RRTs) was performed by integrating the petrophysical values from the plugs and their corresponding well log data of two cored wells using K-means unsupervised classification algorithm. The classification results were combined with various conventional techniques to evaluate the quality and geological characteristics of the studied sequence. This evaluation encompassed different parameters such as flow and storage capacity, reservoir quality index, flow zone indicator, pore spaces interpretation, and average pore and throat radius. The study involved a detailed analysis of thin sections to identify various facies, including shrubstones, reworked, and spherulitestone, and to classify various forms of porosity such as interparticle, intraparticle, intercrystalline, vug, moldic, fracture, and growth framework porosity. Pore Network Modeling from μCT analysis of plugs was used specifically for the characterization of pores and throats of plug samples from each RRT. These datasets were utilized as supporting evidence to offer a more accurate and inclusive knowledge of reservoir quality. The study aimed to develop predictive models by implementing deep learning and machine learning algorithms trained on well log data to estimate plug porosity and rock type. Two deep learning models, ResNet and 1D CNN, were trained and evaluated for plug porosity prediction, with the 1D CNN model showing superior performance. Additionally, the XGBoost algorithm was applied to predict rock type, achieving high accuracy on both the training and validation datasets. The predicted results were compared with actual data to evaluate the effectiveness of the models and were then utilized to estimate plug permeability values. The results demonstrate the potential of deep learning and machine learning approaches in reservoir characterization and management, enabling the evaluation of subsurface reservoir properties even with incomplete datasets, which could lead to an improved understanding of the reservoir properties and better management of the reservoir. This integrated study provides deeper insight into the complex reservoir properties and can help improve decision-making processes and optimize management and production strategies in the challenging pre-salt carbonate reservoirs or similar complex reservoirs.

An experimental assessment of seawater alternating near-miscible CO2 for EOR in pre-salt carbonate reservoirs

Enhanced oil recovery (EOR) methods considering the injection of seawater and CO2 have been widely investigated and applied in the Brazilian pre-salt fields. The high availability of these fluids in offshore facilities makes seawater alternating CO2 (CO2WAG) a viable and environmentally friendly EOR method. It combines the advantages of seawater injection and CO2 injection to improve fluid mobility control and viscous fingering attenuation. In this study, in addition to the core flooding test of secondary seawater flooding and the tertiary CO2WAG, different experimental determinations provided a better understanding of the mechanisms related to the EOR methods applied to a carbonate core composed mainly of dolomite, and their interactions with pre-salt oil, brines and CO2. A 13.30% incremental oil recovery was achieved by alternating seawater with CO2. Considering formation brine, non-carbonated seawater, or seawater saturated with CO2, contact angle measurements revealed that the wettability alteration is not significant when dolomite is slightly water-wet, even in the presence of CO2. On the other hand, measures of brine/oil, brine/CO2/oil and CO2/oil interfacial tension emphasize the beneficial effects of this gas for EOR, in near-miscible conditions. This is achieved by the reduction of capillary and interfacial forces that act by trapping the oil in the pores of the medium. The brine salinity, the presence of magnesium in dolomite and the oil's low TAN/TBN ratio proved to be essential factors in determining the slightly water-wet wettability of the dolomitic rock and the interfacial tension between the phases. Furthermore, for the experiments carried out in the presence of brine with solubilized CO2, a considerable variation in the oil drop volume was observed due to the mass transfer of CO2 between the phases. Finally, experimental results showed that the additional oil recovery was mainly associated with oil swelling, viscosity reduction, and mobility increase, which occur even in near-miscible conditions during CO2WAG.

Water alternative gas (WAG) optimization for a heterogeneous Brazilian pre-salt carbonate reservoir

Abstract Water alternating gas (WAG) is a cyclical process that involves alternating water and gas injections with the primary goal to improve sweep efficiency by maintaining initial high pressure, slowing water and gas breakthrough, and lowering oil viscosity. The objective of this work is to apply and optimize a WAG strategy on a carbonate field with light oil, compare it to the initially planned water-flooding strategy, and investigate the capability of WAG to improve field production. In this research, a compositional reservoir simulator was used to model a WAG process by injecting produced gas into the reservoir, using the same well structure as an optimized water-flooding strategy. Subsequently, a WAG strategy was created, optimizing the number and locations of wells, to facilitate a comparative analysis of the two recovery methods. The WAG optimization involved a detailed assessment of variables such as bottom hole pressure (BHP), WAG cycle duration, maximum gas oil ratio (GOR), and well positioning, to achieve a high net present value (NPV). The study focuses on the application of WAG optimization modeling in unconventional reservoirs, specifically pre-salt carbonate reservoirs, and investigates its implications on production strategy and forecast, emphasizing its potential for maximizing NPV and oil recovery in a recently producing field. The results showed that WAG improved reservoir performance when compared to water injection and produced a greater amount of oil. This solution showed potential to be tested under uncertainties (reservoir heterogeneity, faults, fractures, karsts, vugs, etc.) as future steps.

CO2 degassing in CaCO3 precipitation in the presence of oil: Implications, modeling, numerical simulation, validation, prototype development, and experimental results

Precipitation and scaling are recurring problems in many water-handling processes. Particularly in oil production, such occurrences are critical due to the infeasibility or extreme difficulty of remediating precipitation or removing scale. This is due to adverse operating conditions: high pressures and temperatures, the action of corrosive gases such as CO2 and H2S, high salinity, and a confined system in a rocky medium. Brazilian Pre-Salt carbonate reservoirs are notable for the high CO2 content in their fluids, in which this acid gas becomes a variable that affects several stages of the exploratory process. The relationship between CO2 and calcium carbonate (CaCO3) is evident in the reaction Ca(aq)2++2HCO3 (aq)−⇄H2O+CaCO3 (s)+CO2 (aq). The pressure drop inherent to the production degasses the CO2 (CO2(aq) → CO2(g)), which shifts the equilibrium to the right and implies the formation of CaCO3(s). This paper presents some developments carried out by our research team to theoretically understand the phenomena related to CaCO3 precipitation and scaling in the severe conditions of the Pre-Salt oilfields. Exhaustive bibliographic research, thermodynamic projections, numerical simulations with real data from geothermal fields (without oil) and a Pre-Salt well (with oil), in addition to laboratory experiments in atmospheric conditions were the resources employed to reach the point where the research practically stagnated. This evidenced the need to build an experimental prototype capable of investigating the phenomena related to carbonate precipitation and scaling under conditions as close to the real as possible. We will present the main resources of equipment designed to explore several flow assurance issues, especially those related to calcium carbonate scaling. Some qualitative experiments showed the device's capacity with surprising preliminary results. In such trials, we use real Pre-Salt dead oil, inject CO2 and methane, apply a brine with high salinity, and operate up to 95 °C and 104 bar. We confirmed that CO2 greatly influences the CaCO3 precipitation, but we also observed unexpected phenomena, such as the large size of the aragonite crystals (a CaCO3 polymorph) and the high wettability of the Pre-Salt oil to CaCO3, which significantly altered the rheology of the oily phase.

Core scale investigation of fluid flow in the heterogeneous porous media based on X-ray computed tomography images: Upscaling and history matching approaches

In this paper, experiments and simulations were performed on outcrop samples from Lagoa Salgada in Rio de Janeiro, Brazil, as a possible analog to one of the most typical Brazilian Pre-salt carbonate reservoirs rocks. The rocks were microbial carbonates where plugs comprising two main facies were sampled, simplified as fine-grained and vugular facies. The plugs were utilized to study the impact of pore geometry with both experimental and simulation approaches on recovery factor, saturation profile, and relative permeability estimations. To provide direct visualization of the geometry, description of pore structure, and calculation of concentration profiles, computed tomography (CT) imaging was integrated with experimental measurements of petrography and core flooding. The injection of two pore volumes of formation water resulted in a recovery factor between 28 and 34 percent for the plug samples. Furthermore, based on porosity generated by dry and wet CT, as well as saturation profiles resulting from CT data collected during drainage and imbibition processes along the length of the plugs, it is revealed that the distribution of these properties was diverse and heterogeneous. An algorithm was used to process the 2D tomography images of the samples to remove the region related to the exterior parts. The images were then stacked to create a 3D fine-scale grid to simulate the porous media and the fluid flow by applying rules for the segmentation of rock types, porosity, and permeability estimations of each grid block. Course-scale grids were created by applying upscaling techniques to reduce computation time. Simulated produced fluid cuts for different upscaled models were compared with the experimental results from core flooding. A history-matching technique was then applied to match experimental and simulation results, calculating the relative permeability of two main defined facies and creating an updated model capable of assessing past and present performance and future forecasting. Since relative permeability is essential for accurate simulation, estimating these curves in the heterogeneous pre-salt reservoir considering different facies, greatly influences reasonable future prediction performance and the ability to make informed operational decisions.