Core Plugs Research Articles

Sandstone wettability in supercritical CO2-brine-rock interactions evaluated with 13C and 1H magnetic resonance

During the first decades of geologic CO2 storage in saline formations and depleted reservoirs, structural trapping is the most important storage mechanism. The effectiveness of CO2 containment hinges on the assumption that the sealing formation remains water wet in the presence of dense CO2. In this work, multiple 13C and 1H magnetic resonance (MR) methodologies were employed for the first time to evaluate the interactions between supercritical CO2, brine, and the pore surface of a Berea sandstone core plug under reservoir conditions. These studies employed a novel variable field superconducting MR and magnetic resonance imaging (MRI) instrument which permitted sequential 1H and 13C measurements of core plugs at high-pressure and high-temperature. To systematically study the wettability of rock core exposed to supercritical CO2, four experiments were designed including bulk CO2 in a high-pressure vessel, bulk CO2-brine, 13CO2 in dried rock core, and a 13CO2-brine-rock experiment.The measured 13C and 1H MR relaxation times in this work indicate that the Berea sandstone remained strongly water-wet when the brine saturated core plug was exposed to supercritical CO2 under reservoir conditions. For both 13C and 1H, T1 relaxation times provide more reliable wettability evaluation as compared to T2 due to the impact of molecular diffusion through internal magnetic field gradients. One-dimensional (1D) MRI was employed to spatially resolve 13CO2 and brine in the core plug. Two-dimensional (2D) MRI was able to image 13CO2 and brine in a PEEK vessel. The quantities of CO2 and brine in the core plug were determined from the MR signal intensities of 13CO2 and brine.

Analyzing the wettability changes of rocks in various states of core plugs

Current core plugs preparation standards for laboratory studies are developed for water-wet reservoirs and do not consider other types of wettability. Researching how different core preparation methods affect laboratory studies and wettability changes is relevant and important for petrophysical reserve estimation. Preconditions of doing this work was the question how core plugs impacts wettability changes in carbonate formations from several Eastern Siberian fields. The article describes the SCAL results of measuring the USBM wettability on core plugs at various states: a core plug with preserved saturation (before extraction), a core plug after extraction, and a core plug after wettability restoration. The authors showed how each of the stages of core plugs preparation affects wettability changes in rocks, the study of which is complicated by strong diagenetic changes: uneven salinization, bituminization, and anhydritization. The most accurate results were obtained from core plugs with preserved saturation. Overall, wettability of core plugs shifted towards a more hydrophilic state after extraction, but extraction did not fully change wettability from hydrophobic to hydrophilic.

Back propagation neural network model for controlling artificial rocks petrophysical properties during manufacturing process

Artificial rocks are increasingly used in experiments, and it is important to make artificial rocks’ petrophysical properties similar to real rocks to obtain more valuable results. The effect of widely used five factors, grain size (GS), grain size distribution (GSD), mass fraction of cementing agent (MC), pressing pressure (PP), and pressing time (PT), on artificial rock petrophysical properties are analyzed. Three factors, GS, MC, and PP, which are suitable for establishing a quantitative model are opted. The relationships of 80 rock plugs’ petrophysical properties and manufacturing factors are studied, which indicates MC and PP are negatively correlated with porosity and permeability, and GS has a significant effect on permeability but little effect on porosity. Furthermore, a novel back propagation (BP) neural network model is proposed, which can be used to determine factor values during artificial rock manufacturing process. A series of artificial core plugs are manufactured relying on manufacturing factor values calculated by the BP neural network model, and their petrophysical properties are tested and compared with design petrophysical properties value to verify the model. Verification results show that comprehensive average error of porosity and permeability of artificial rock, including calculating error and manufacturing error, is 2.38 and 18.68%, respectively.

Prediction of shear wave velocity in three sedimentary rocks in East Baghdad oilfield using multiple regression analysis

Shear wave is a crucial parameter for assessing the wellbore stability, the stress response, and rock deformation. It is essential for constructing the mechanical earth model (MEM) for many applications related to reservoir geomechanics including wellbore stability, sand production, hydraulic fracturing, and fault reactivation. However, shear sonic data is often omitted during the well-logging measurements for cost and saving purposes. To overcome this challenge, recent research has been focused on determining shear wave velocity through the use of core plugs, empirical correlations, artificial intelligence techniques, and multiple regression to quantify and evaluate the mechanical properties of subsurface formations without performing direct measurements at the wellbore. The greatest difference between this study and the literature is to predict the shear wave velocities for three sedimentary rocks based on conventional well logs. This study has been conducted on datasets of two wells drilled in the East Baghdad oilfield, for which there is a lack of shear wave data. Two formations (Tanuma and Zubair formations) within the production section of this field were conducted to develop new models for determining the shear wave velocity using multiple regression analysis. These two formations primarily consist of three lithologies: limestone, sandstone, and shale. Before the model development, data analysis on the selected data was applied to figure the most influential parameter(s) in determining the shear wave velocity. The results of the developed models are then compared with the previous models in the literature. The results showed that the multiple regression analysis technique is a powerful technique in determining shear wave velocity with high-performance capacity. The correlation coefficient ( ) and the root mean square error (RMSE) were 0.84 and 0.092 for limestone, 0.84 and 0.0972 for sandstone, and 0.86 and 0.0796 for shale respectively. Furthermore, the performance of the developed models is well matched to the actual shear wave data rather than the Castagna correlations. The findings of this study are effective in determining shear wave velocity for future applications related to reservoir geomechanics without needing costly well-log or core measurements.

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.

Comparative evaluation of pore volume compressibility of carbonate reservoir rocks: different laboratory measurement approaches

The pore volume compressibility (C PV) of a reservoir plays an essential role in estimating the reserve oil and recovery factor. Therefore, selecting an appropriate laboratory measurement approach for determining the C PV is crucial. This study aims to compare three different routine approaches to C PV measurement. Fifty-eight carbonate core plug samples with diverse porosity from the Sarvak Formation in the Southwest of Iran were selected. The measurements were performed at different saturation, pressure, and temperature conditions in triaxial core holders. Results show that samples with the lowest porosity have the highest compressibility value, and samples with the highest porosity have the lowest value. Furthermore, the compressibility measured on brine-saturated cores at pressure and temperature conditions was higher than only brine-saturated, and consequently higher than dry core plugs. Hence, the measurement methods and approaches severely affect the resultant compressibility. The values obtained at representative reservoir conditions are advised to be utilized in simulation and modeling studies. A novel reciprocal model was also proposed to appropriately correlate the data with porosity. The results of this work give insight into the selection of the best laboratory measurement approach to estimate the actual C PV value in reservoir conditions, especially at varying pore pressure and temperature.

Graphene Nanoplatelets Extend Life of Scale-Inhibitor Squeeze Treatment

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215228, “Graphene Nanoplatelets for Extended Lifetime of Scale-Inhibitor Squeeze Treatment in a High-Temperature Reservoir,” by Suzalina Zainal, SPE, Norzafirah Razali, and Mohamad A. Rodzali, Petronas, et al. The paper has not been peer reviewed. _ Scale-inhibitor squeeze (SISQ) treatment is an established method for offshore fields that allows an extended effectiveness of scale inhibitors in preventing deposition over time. One of the primary issues in SISQ campaigns is the short squeeze lifetime of less than 1 year. The study detailed in the complete paper proposed graphene nanoplatelets (GNP) as a preflush system to extend the lifetime of a conventional SISQ treatment. This carbon-based nanomaterial allowed enhanced adsorption of the phosphonate-based scale inhibitor. GNP as a Preflush System A high-surface-area GNP preflush system was chosen to condition the rock surface to overcome the apparent lack of suitable surfaces available for scale-inhibitor adsorption during SISQ treatment. The GNP was injected to coat the rock surface. GNPs consist of a few graphite layers with thicknesses varying from 0.7 to 100 nm. The carbon-based nanomaterial forms a honeycomb structure, regarded as a good alternative to its predecessor, graphene, because of its lower cost and potential for large-scale production. GNP particle size ranges between 100 and 200 nm. This 2D carbon nanomaterial offers several advantages, such as high surface area, a high aspect ratio with a planar shape, and good mechanical properties with excellent thermal and electrical conductivities. It is also inert toward common reservoir fluid. Experimental Procedure Materials. Injection and formation water (brine samples) were prepared based on compositions listed in Table 1 of the complete paper. Berea core plugs were used for static-adsorption and injectivity experiments. In these two experiments, the core samples were used to provide similar rock properties when comparing performances of the baseline preflush (seawater) vs. nano-preflush systems. The average rock permeability for the candidate oil field is between 200 and 400 md. Dispersion Evaluation in High Divalent Brine. Gum arabic (GA) stabilized the GNP in high divalent brine. The polymer-grafted GNP (P-GNP) samples were evaluated in terms of exfoliated sites as compared with GNP alone. Zeta-potential and particle-size analysis also were performed at different P-GNP concentrations. Static-Adsorption Evaluation. A static-adsorption method was designed to replicate preflush injection of P-GNP before introduction of scale inhibitor. Experiments compared the adsorption of the scale inhibitor onto crushed Berea rock, precoated with P-GNP, with another without pre-coating that used seawater preflush only. Coreflood Evaluation. Because of the scarcity of the native core samples, only Berea core samples were used for the injectivity study, while native core samples were used for the SISQ adsorption/desorption coreflood evaluation. In both types of experiments, a P-GNP preflush system was compared with the baseline (seawater preflush).

Quantification of the effect of fracturing on heterogeneity and reservoir quality of deep-water carbonate reservoirs

The Shiranish Formation represents one of the most important fractured reservoirs in northern Iraq. In this work, the petrophysical properties of the formation have been fully characterised using microscopy, core analysis, and well log analysis using conventional methods as well as new quantitative diagenetic approaches. During this work we have developed methods to quantify a petrophysical heterogeneity index (χ), reservoir quality indicator (RQI), and fracture effect index (FEI) for each of the stratigraphic units of the formation. The FEI was calculated by dividing the difference between the mean permeability of the wireline log data and the mean permeability of the unfractured core plug samples by the difference between the mean porosity of the wireline log data and the mean porosity of the unfractured core plug samples. This study shows that the Shiranish Formation has a fracturing pore system in all the characterised units, but it is particularly well developed in U.4, which shows the best reservoir quality (A and B). The new methods developed in this study can be applied to any carbonate formation to provide a trustworthy way to obtain a reservoir quality indicator linked to the petrophysical heterogeneity of the studied formation.

Applying machine learning for hydraulic flow unit classification and permeability prediction: case study from carbonate reservoir in the Southern part, Song Hong basin

Machine learning (ML) is an artificial intelligence (AI) that enables computer systems to classify, cluster, identify, and analyze vast and complex sets of data while eliminating the need for explicit instructions and programming. For decades, machine learning has become helpful for complex reservoir characterization such as carbonate reservoirs. Permeability prediction from well logs is a significant challenge, especially when the core data is rarely available due to its high cost. In this study, we aimed to bridge this gap by demonstrating the practical application of integrating Hydraulic Flow Units (HFU) and machine learning methods. Our goal was to provide a reliable estimation of permeability using core and wireline logging data in the complex Middle Miocene carbonate reservoir of the CX gas field in the southern part of the Song Hong basin. In the first step, due to the reservoir’s heterogeneity, the core plug dataset was classified into 5 HFUs based on the flow zone indicators (FZI) concept from the modified Kozeny-Carman equation using unsupervised machine learning - K-means method. The porosity - permeability for each HFU was defined after HFU clustering. In the second step, we designed three different workflows to predict permeability and HFU using supervised machine learning from a combination of core and log data. These workflows were rigorously test and compared with the core data. The most accurate result was chosen as the base, providing a high confidence level in our predictions’ reliability.

Diagenesis including cataclastic band development in the Permian Penrith Sandstone, Vale of Eden Basin, England

Diagenesis in the Penrith Sandstone is characterized by early hematite and mixed illite/smectite cementation, followed by burial compaction, feldspar and two episodes of quartz cementation. The primary quartz overgrowths are characterized by heterogenous luminescence; however, the secondary quartz overgrowths are characterized by thinner and darker luminescence. Cataclasis post-dates primary quartz cementation, and significantly reduces grain and pore aperture size. The apex of mercury volume for a deformed sample was reduced up to three times in comparison with the undeformed rock. Dissolution occurred during cataclasis as authigenic hematite was removed in deformation zones, improving pore aperture size and consequently enhancing sandstone porosity and permeability. Recent fracturing created fractured-pores and improved porosity and permeability in tight cataclastic samples. Evidence for syn-cataclastic dissolution is observed in the samples studied. This is indicated by the dissolution of authigenic feldspars and the enhancement of poroperm parameters adjacent to cataclastic zones and the absence of hematite cement within them. Based on those the sequence of diagenetic evolution in the Penrith Sandstone can be reconstructed. Host samples were characterized by good to very good poroperm values, varying between 20 and 24% porosity and from 809÷1445 mD permeability. Cataclastic core plugs have 13÷21% porosity and 0.12÷39 mD permeability. The porosity reduction by cataclasis was estimated to be as much as 4.5% on average. Fracturing and dissolution improved poroperm parameters in studied samples. Recently fractured core plugs have about 292 mD permeability on average. Dissolution-cataclastic samples have 32% porosity and 18 mD permeability, whereas dissolution-host samples have 31% porosity and maximum permeability as much as 2469 mD on average. Cataclasis occurred in combination with in situ significant reservoir dissolution and fracturing may improve a sandstone reservoir in excellent quality.

Integrating μCT imaging of core plugs and transfer learning for automated reservoir rock characterization and tomofacies identification

Traditional methods of core characterization are time-consuming and require the considerable effort of a large number of experts. At the same time, it is quite difficult to readily detect small but important elements in reservoir rocks, especially inside the core volume, that can have a strong impact on assessing reservoir potential and hydrodynamic properties. This research explores the integration of high-resolution micro-computed tomography (μCT) imaging and transfer learning for the automated characterization of reservoir rocks and tomofacies identification. The study involved collecting and marking a dataset containing 66,560 μCT images of 130 standard core plugs containing all major reservoir rock types. Using this dataset of 2D μCT images of core plugs, we applied convolutional neural networks (CNNs) pre-trained on ImageNet and fine-tuned them for rock classification tasks. Applying a transfer learning approach, we trained seven ResNet-50 models, which were able to identify and classify reservoir rock features in μCT images. These features included basic characteristics such as rock type, general texture, the presence of fractures and sulfidization that are common for all reservoir rocks. Further, depending on a specific rock type, individual features such as grain size, individual sedimentological texture and the presence of organic matter zones in the sample could be determined by the specialized model. The results show an average classification accuracy of over 94%, indicating the effectiveness of transfer learning in enhancing rock characterization. The obtained models demonstrated high validation rates and were organized into a workflow for automated rock feature characterization. A case study conducted on a carbonate core from a real oilfield provided a practical demonstration of the automated system's work, whose predictions were validated by traditional analyses such as X-ray diffraction and thin-section petrography. The produced models demonstrated the ability for rapid detection of subtle details that might otherwise have been missed during manual inspection. In addition, the concept of tomofacies resulting from the integration of μCT images and machine learning predictions has proven useful in highlighting different reservoir zones, allowing us to understand their heterogeneity and the ability to separate rock sections despite their apparent monotony. These findings suggest that the integration of μCT imaging and transfer learning is a promising approach for improving the automation and accuracy of reservoir rock characterization. The developed technique represents a significant advance in reservoir characterization, offering rapid and accurate identification of rock properties that can improve exploration and development strategies.

Improved Amott Method to Determine Oil Recovery Dynamics from Water-Wet Limestone Using GEV Statistics

Counter-current spontaneous imbibition of water is a critical oil recovery mechanism. In the laboratory, the Amott test is a commonly used method to assess the efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell experiment estimates ultimate oil recovery, but not the recovery dynamics that hold fundamental information about the imbibition mechanisms. Retention of oil droplets at the outer core surface and initial production delay are the two key artifacts of the classic Amott experiment. This retention, referred to here as the “external-surface oil holdup effect” or simply “oil holdup effect”, often results in stepwise recovery curves that obscure the true dynamics of spontaneous imbibition. To address these holdup drawbacks of the classic Amott method, we modified the Amott cell and experimental procedure. For the first time, using water-wet Indiana limestone cores saturated with brine and mineral oil, we showed that our improvements of the Amott method enabled accurate and reproducible measurements of oil recovery dynamics. Also for the first time, we used the generalized extreme value (GEV) statistics to describe oil production histories from water-wet heterogeneous limestone cores with finite initial water saturations. We demonstrated that our four-parameter GEV model accurately described the recovery dynamics, and that optimal GEV parameter values systematically reflected the key characteristics of the oil–rock system, such as oil viscosity and rock permeability. These findings gave us a more fundamental understanding of spontaneous, counter-current imbibition mechanisms and insights into what constitutes a predictive model of counter-current water imbibition into oil-saturated rocks with finite initial water saturation.

Capillary pressure profile estimation using numerical method and centrifuge test data

Capillary pressure is a crucial parameter that affects the displacement of two or more immiscible fluids in porous media. Measuring capillary pressure as a function of saturation is essential for simulating the process of immiscible flooding in porous media, especially in oil reservoir rocks. The centrifuge method is one of the most widely used techniques for estimating capillary pressure in reservoir rock porous media. This study applied a numerical method to a one-dimensional equation with boundary conditions to simulate the flow of two immiscible fluids in the core plug for a centrifuge experiment. The study also tested oil-water and air-oil systems across various core plugs using a centrifuge device. It involved analyzing the experimental data output through a numerical calculation method to derive the capillary pressure correlation as a function of saturation. The correlation obtained for capillary pressure demonstrates an acceptable match with the experimental data and is applicable in other simulation software.

Bridging the gap: Integrating static and dynamic data for improved permeability modeling and super k zone detection in vuggy reservoirs

Permeability modeling in fractured and vuggy reservoirs presents significant challenges, especially in carbonate reservoirs like Brazil’s Barra Velha Formation. The interpretation of vug properties is often subject to misconceptions. It is common to mistakenly consider vugs as part of the matrix, attributing uniform porosity and permeability properties. Alternatively, they are sometimes regarded as fractures, attempting to replicate the influence on permeability enhancement. However, vugs exhibit distinct behavior compared to fractures. Their characteristics are contingent upon factors such as geometry, size, and their relationship with the matrix. Existing methods often overlook the substantial impact of vuggy porosity, leading to inadequate representation of permeability values obtained from core plug measurements or downhole static data, such as Nuclear Magnetic Resonance (NMR) logs. In contrast, dynamic data derived from drill-stem tests (DSTs) and inferred from the Productivity Index (J) provide a more holistic view of the reservoir’s permeability, yet typically yielding a single permeability value for each interpreted interval. This research introduces a novel methodology that addresses these challenges by integrating static and dynamic data, with a primary focus on vuggy porosity using a permeability indicator from a dynamic source. A key innovation lies in the development of a method for estimating total permeability in vuggy intervals, accounting for the effects of vugs and calibrating permeability with dynamic data such as J, DST and Production Logging Tests (PLT). We substantiated the impact of vugs on the augmentation of permeability and production through the application of a localized reservoir simulation model around a key well. Two sensitivity analyses were conducted, one employing a grid representing matrix permeability and another incorporating total permeability with adjustments accounting for the influence of vugs. Additionally, we present two approaches for estimating vuggy porosity: one based on acoustic WellBore Image (WBI) and the second through image segmentation, which can be applied universally across different wellbore image formats. Furthermore, this study explores the concept of superkzones, representing intervals with exceptionally high permeability. The partitioning coefficient (CP), quantifying the relationship between vuggy porosity and total porosity, is employed to generate a probability curve for the occurrence of superkzones in intervals lacking production data. This curve accounts for critical factors such as pressure drop and fluid viscosity, providing a more comprehensive understanding of reservoir behavior. Through a comprehensive case study, our research aims to shed light on the intricate permeability characteristics of the Barra Velha Formation, while identifying the presence of superkzones. The proposed methodologies offer a bridge between static and dynamic data, resulting in a continuous permeability curve that aligns more closely with production data. Ultimately, this work contributes valuable insights for reservoir management and the production strategies optimization in complex carbonate reservoirs within the Santos Basin.

Reservoir evaluation of dolomitized Devonian strata in the Western Canada Sedimentary Basin: implications for carbon capture, utilization, and storage

Abstract Differentially dolomitized carbonate strata in the Western Canada Sedimentary Basin (WCSB) are increasingly targeted for carbon capture, utilization, and storage (CCUS), yet few studies have evaluated the petrophysical characteristics of these conventional hydrocarbon reservoirs for this purpose. To address this, this study uses drill-core analysis (sedimentology, diagenesis, pore morphology, and distribution), together with core-plug and production data, to evaluate the properties of five depleted oil and gas fields in the Middle to Upper Devonian Swan Hills Formation, Leduc Formation and Wabamun Group. The Swan Hills and Leduc formations are composed of reef, shoal, and lagoon deposits that are predominantly fossil-rich (e.g., stromatoporoid-dominated rudstones and boundstones). In contrast, the carbonate-ramp deposits of the Wabamun Group are fossil-poor, consisting instead of variably bioturbated carbonate mudstones, wackestones, and packstones. Replacement dolomitization is variable throughout each stratigraphic unit, but generally occurs within fossil-rich and/or heavily bioturbated intervals. Fracture densities are broadly comparable in limestone and dolostone. Porosity in the Swan Hills and Leduc formations is predominantly moldic and vuggy, occurring where fossils (e.g., stromatoporoids) are partially or fully dissolved. Pore space in the Wabamun Group is mostly restricted to intercrystalline porosity in burrows. In general, burial cements (e.g., calcite and dolomite) are volumetrically insignificant and only partially fill pores. Exceptions to this include porosity-occluding cements associated with fractures and breccias in the vicinity of faults. Dolomitization and depositional facies are found to exert a strong control on pore morphology, distribution, and interconnectivity. Porosity is principally controlled by the relative abundance of skeletal grains and by the presence of burrows. These highly porous facies acted as fluid pathways during burial diagenesis, resulting in their preferential dolomitization, solution enhancement of pre-existing pores, and creation of volume reduction-related porosity. The high CO2 storage capacity and low unplanned plume migration risk (due to depositional and/or diagenetic baffles) of dolomitized reefal reservoirs (e.g., Swan Hills and Leduc formations) make them more attractive targets for CCUS than those with limited capacity and/or potential migration pathways (e.g., fault-related fractures and breccias in the Wabamun Group). These results demonstrate that drill-core analysis, in combination with legacy data, can provide valuable insights into the factors that control reservoir CO2 injectivity, plume migration, and storage capacity.

Estimation of pore-type distribution utilizing petrophysical data and rock physics modeling on an Iranian carbonate reservoir

Pore types in carbonate reservoirs are more complex than their sandstone counterparts due to the wide spectrum of their depositional environments and their more complicated post-depositional processes. This means that a good knowledge of pore types is vital in determining carbonate formation’s elastic and reservoir properties. This study aims to develop a multi-physics approach to determine pore-type variations in a carbonate reservoir using well log information from one of the oilfields of the Abadan Plain in southwest Iran. Firstly, we determined lithology, porosity, and fluid content by interpreting conventional well logs (gamma ray, resistivity, density, neutron, photoelectric, and P-wave sonic). Then, nuclear magnetic resonance data were used to determine different pore types within the Main Ilam and Sarvak formations. We distinguished between clay, micro, meso, and macro pore types. We confirmed our interpretation results using thin sections, scanning electron microscopy photographs, and pore-size distribution on the available core plugs. Finally, a carbonate rock physics model was employed to model sonic velocities using petrophysical interpretation along with pore-type determination results. A good match between modeled and measured sonic velocities confirmed that using nuclear magnetic resonance data for pore-type determination can reasonably estimate pore-type variations needed for rock physics modeling. The standard industry procedure for carbonate rock physics modeling uses sonic logs, core data, or thin sections to determine pore types. We offer a substitute approach with reasonable accuracy for pore-type modeling needed for carbonate rock physics modeling. We modeled pore types independently from sonic velocity and used them to predict P-wave velocity with a correlation coefficient of 92 and 64 percent accuracy in the Main Ilam and Sarvak formations.Graphical abstract

Właściwości fizyczne zbiorników łupkowo-piaskowych: Pole Szafranowe, Delta Nilu, Egipt

The Saffron gas Field is in the Scarab-Saffron Development Lease in the offshore Nile Delta. It was discovered by the Saffron-1 exploration well drilled in 1998 and appraised by Saffron-2 and Sapphire-3 wells. Saffron is a stacked channel system and consists of 6 different reservoirs with differing levels of connectivity between them. It can be interpreted as deep-water canyon fill deposits on a delta-front slope. Some physical properties of 4 full diameter core samples (approximatly164 core plugs) obtained from the Saffron-2 borehole were petrophysically analysed. Helium porosity, horizontal and vertical permeability, grain density and electrical resistivity were laboratory measured. Several bivariant plots were accomplished such as porosity- permeability; grain density, formation resistivity factor; cementation exponent and Winsaur’s multiplier (a) as well. Several regression line equations with robust coefficient of correlations were obtained to be used for reservoir characterization. On the other hand, numerous frequency histograms were built for most of the measured reservoir parameters to determine their type of distribution and other statistical parameters. Some important relations like cementation exponent versus multiplier (a) are performed which improves Archie’s general equation and subsequently the reservoir fluid saturation (Sw and/or Sh). The lack of stratification in sedimentary section represented by core numbers 4&5 of Saffron-2 well have severe consequences on measured reservoir parameters especially exposed by the porosity- permeability relation.

Determine Oil and Water Saturations in Preserved Source Rocks From 2D T1-T2 NMR

Two-dimensional (2D) T1-T2 NMR has been widely proposed as a method to determine the fluids present in unconventional source rocks. However, the assignment of the components in the 2D T1- T2 NMR spectra has so far been based on conceptual consideration and lacks rigorous experimental verification. Many assignment variations appeared in the literature and can be misleading. For example, large T1/T2 peaks in the 2D T1-T2 NMR were suggested to be fluid in small pores coupled with kerogen solid through dipolar relaxation. Our recent 500-MHz NMR relaxation experiments found that the dipolar relaxation between nanoconfined fluids and solid matrix is not big enough to support that large T1/T2 interpretation. The objective of this paper is to determine what quantitative data can be obtained using 2D T1-T2 NMR from source rocks with high confidence. We found the oil and water saturation can be accurately measured in preserved source rock plugs. Two-dimensional T1-T2 NMR data were collected on preserved core plugs from five wells of a source rock reservoir using an inversion-recovery Carr-Purcell-Meiboom-Gill (CMPG) pulse sequence on a 12-MHz NMR instrument. The acquired 2D data were inverted using an optimized inversion software, MUPen2D. We then obtain oil and water content in the plug from the 2D T1-T2 NMR using an in-house-developed NMR MATLAB app. The porosity of all the plugs was measured using a combined NMR and gas porosimetry (CNG) method. Oil and water saturation were also obtained using an industry-standard method developed by the Gas Research Institute (GRI) on the rock material close to where the plug was drilled. The oil and water saturations measured on the preserved plugs using 2D T1-T2 NMR and CNG are consistent with those from the GRI method using crushed rocks and an invasive cleaning procedure. The results show that oil and water saturations were accurately determined from 2D T1-T2 NMR on preserved source rock samples with high confidence. The NMR method is nondestructive and noninvasive and takes less than 4 hours on a preserved source rock plug, while GRI is destructive and invasive and can take several weeks for an accurate measurement on one sample. The measured results can be further used to determine the production potential of a source rock well in combination with log data.

The Role of Core Sample Geometry on Countercurrent Spontaneous Imbibition: Mathematical Foundation, Examples, and Experiments Accounting for Realistic Geometries

Summary Countercurrent spontaneous imbibition (SI) experiments are among the most common multiphase experiments performed on porous rock samples. Although the samples rarely are designed to give linear flow, they are often modeled and interpreted using mathematical descriptions assuming linear flow. In this work, the goal is to derive general understanding of how imbibition into different sample geometries behaves compared with linear (1D) imbibition. Using the mathematical theory of N-volume spheres (N being the dimension), we consider core samples as N-spherical and quantify their geometry by a dimension N and length scale L. For the special cases, N=1,2,3, we obtain linear, radial, and spherical flow; however, we treat the dimension as an arbitrary real number for cases not adhering to either of these regimes. Particularly, for rectangular or cylindrical core plugs, a continuous range of dimensions is produced. Theoretical calculations of N and L of arbitrary sample shapes are derived based on relations with area per volume and derivative of area with respect to volume. They correctly produce limit cases and physically meaningful values for symmetrical, cylindrical, and rectangular geometries. The differential equation for countercurrent imbibition in N-dimensions is derived and solved with numerical examples. Also, a simplified analytical solution assuming piston-like displacement is derived to get illustrative relations between system parameters (including dimension) and recovery and front position. Predicted recovery profiles of the N-dimensional (N-D) solution overlap consistently with numerical simulations (by an alternative simulator) into cylindrical geometries with a wide range of height/diameter ratios and viscosity ratios. At early time, the saturation profiles are self-similar (look the same plotted against position divided by square root of time) and identical regardless of dimension. As long as the profiles are self-similar near the open boundary, recovery is proportional to the square root of time. For N=1, this lasts long after the front has reached the closed boundary, while for N >1, it can happen long before the boundary has been reached. The same time scale was applicable for all geometries, stating especially that doubling the length scale increased the time of the entire recovery profile by a factor 4. As long as recovery is proportional to square root of time, at a given time, it is also proportional to dimension over length, NL, and the time needed to reach same level of recovery is proportional to LN2. Permeability anisotropy (lower vertical than horizontal permeability) could effectively be modeled using an effective increased height, which further was captured by the dimension and length scale. Literature and in-house experimental data were matched by the model and used to validate model predictions such as the variation in time, shape of recovery curves with changes in dimension, and the importance of accounting for the dimension (geometry) during data interpretation. The model is valid for all wetting states but assumes negligible gravity and compressibility effects.

Quantitative characterization of 3D pore structures and percolation characteristics in bioturbated reservoir media based on X-ray micro-CT: a case study of the Neogene Sanya Formation in the Qiongdongnan Basin, Northern South China Sea

Organisms alter the primary texture of sediments, leading to alteration in petrophysical properties mediated by a textural and mineralogical contrast between burrow-fill and sediment host, which affects reservoir properties and fluid flow characteristics. In this article, in order to understand the microscopic pore structure and flow state of fluids in microscopic pores of bioturbated reservoirs, Ophiomorpha-bearing bioturbated reservoirs in the Neogene Sanya Formation of the Qiongdongnan Basin in the northern South China Sea were selected to research. Micro-CT was applied to scan selected core plugs, and a 3D pore structure model was established. The geometric characteristics of the microscopic pore structure were quantitatively and visually characterized by a modified maximal ball algorithm, and connectivity analysis of the pore structure was carried out. Numerical simulations of the percolation characteristics of the analyzed bioturbated reservoir samples were performed using digital core software (Avizo) and multi-physics field simulation software (Comsol). The results show that: (1) 3D pore structures reveal that pore volume, pore area, pore equivalent radius, throat area, throat equivalent radius and throat length have a large distribution range; among them, the pore volume has the largest distribution range, which can vary by six orders of magnitude, indicating that the pore size distribution of the bioturbated reservoir is uneven and has strong heterogeneous characteristics; (2) the connected pore structure is very complex, and as the equivalent radius of connected pore increases, the coordination number also gradually increases, the better the connectivity. Numerical percolation simulation results also suggested that larger connected pore space plays a key role in the effective permeability of the reservoir. This study has important implications for analyzing the modification effect of bioturbation on oil and gas reservoirs, and enhancing production and recovery in the study area.