Capillary Pressure Curves Research Articles

Study on Compatibility between Complex Mode Micropore Structure and Polymer Solution of Different Formulation for Conglomerate Reservoir

In this paper, the conglomerate reservoir is selected as the object to investigate the micropore structure and the compatibility of polymer solutions. Firstly, the characteristics of complex mode pore structure are analyzed based on casting thin sections, scanning electron microscope, and capillary pressure curve. Then the conglomerate reservoir is divided into five types by use of the K-means clustering algorithm, and the differences in micropore structure among the different reservoir types are also clarified. Secondly, the dynamic light scattering technology is used to directly determine the hydrodynamic diameter of different polymer formulations. As the polymer molecular weight increases, the average hydrodynamic diameter becomes larger, and with the same polymer molecular weight, the average hydrodynamic diameter becomes gradually larger as the solution concentration increases. Based on the above research results, the matching relationship between five reservoir types and polymer solutions is determined through laboratory experiments. The experimental results show that when the polymer molecular weight is determined, the volume of pore volume that can be effectively swept by polymer hydration molecules gradually decreases as the concentration of the solution increases. When the polymer molecular weight and its concentration are both determined, the pore volume of effective displacement of polymer-hydrated molecules also gradually reduces with becoming worse reservoir pore structure. The scope of application of different polymer formulations becomes progressively smaller as the microscopic pore structure of type I to type V reservoirs becomes deteriorated. The compatibility between the micropore structure of different conglomerate reservoir types and polymer solution is determined to provide the geological basis for the reasonable formulation of the polymer flooding scheme.

Application of Machine Learning to Interpret Steady-State Drainage Relative Permeability Experiments

Summary A meticulous interpretation of steady-state or unsteady-state relative permeability (Kr) experimental data is required to determine a complete set of Kr curves. In this work, different machine learning (ML) models were developed to assist in a faster estimation of these curves from steady-state drainage coreflooding experimental runs. These ML algorithms include gradient boosting (GB), random forest (RF), extreme gradient boosting (XGB), and deep neural network (DNN) with a main focus on and comparison of the two latter algorithms (XGB and DNN). Based on existing mathematical models, a leading-edge framework was developed where a large database of Kr and capillary pressure (Pc) curves were generated. This database was used to perform thousands of coreflood simulation runs representing oil-water drainage steady-state experiments. The results obtained from these simulation runs, mainly pressure drop along with other conventional core analysis data, were used to estimate analytical Kr curves based on Darcy’s law. These analytically estimated Kr curves along with the previously generated Pc curves were fed as features into the ML model. The entire data set was split into 80% for training and 20% for testing. The k-fold cross-validation technique was applied to increase the model’s accuracy by splitting 80% of the training data into 10 folds. In this manner, for each of the 10 experiments, nine folds were used for training and the remaining fold was used for model validation. Once the model was trained and validated, it was subjected to blind testing on the remaining 20% of the data set. The ML model learns to capture fluid flow behavior inside the core from the training data set. In terms of applicability of these ML models, two sets of experimental data were needed as input; the first was the analytically estimated Kr curves from the steady-state drainage coreflooding experiments, while the other was the Pc curves estimated from centrifuge or mercury injection capillary pressure (MICP) measurements. The trained/tested model was then able to estimate Kr curves based on the experimental results fed as input. Furthermore, to test the performance of the ML model when only one set of experimental data is available to an end user, a recurrent neural network (RNN) algorithm was trained/tested to predict Kr curves in the absence of Pc curves as an input. The performance of the three developed models (XGB, DNN, and RNN) was assessed using the values of the coefficient of determination (R2) along with the loss calculated during training/validation of the model. The respective crossplots along with comparisons of ground truth vs. artificial intelligence (AI)-predicted curves indicated that the model is capable of making accurate predictions with an error percentage between 0.2% and 0.6% on history-matching experimental data for all three tested ML techniques. This implies that the AI-based model exhibits better efficiency and reliability in determining Kr curves when compared to conventional methods. The developed ML models by no means replace the need to conduct drainage coreflooding or centrifuge experiments but act as an alternative to existing commercial platforms that are used to interpret experimental data to predict Kr curves. The two main advantages of the developed ML models are their capability of predicting Kr curves within a matter of a few minutes as well as with limited intervention from the end user. The results also include a comparison between classical ML approaches, shallow neural networks, and DNNs in terms of accuracy in predicting the final Kr curves. The research presented here is an extension of the state-of-the-art framework proposed by Mathew et al. (2021). However, the two main aspects of the current study are the application of deep learning for the prediction of Kr curves and the application of feature engineering. The latter not only reduces the training/testing time for the ML models but also enables the end user to obtain the final predictions with the least set of experimental data. The various models discussed in this research work currently focus on the prediction of Kr curves for drainage steady-state experiments; however, the work can be extended to capture the imbibition cycle as well.

Measurement and modelling of dynamic fluid saturation in carbon reinforcements

We propose a methodology to monitor the progressive saturation of a non-translucent unidirectional carbon fabric stack through its thickness by means of X-ray radiography and extract the dynamic saturation curves using image analysis. Four constant flow rate injections with increasing flow speed were carried out. These were simulated by a numerical two-phase flow model for both capillary and viscous leading flow conditions. The hydraulic functions describing pressure and relative permeability versus saturation were determined by fitting the saturation curves using a heuristic optimization routine. As the fluid velocity increases and the flow regime at the flow front shifts from capillary to hydrodynamically driven, the resulting capillary pressure curves for a given saturation level are shifted to higher values, from negative to positive. These as well as the capillary pressure calculated from the pressure drop within the unsaturated region of the fabric correlate well with a corresponding change in the averaged dynamic contact angle.

Evaluation of irreducible water saturation by electrical imaging logging based on capillary pressure approximation theory

One of the most important metrics for evaluating oil and gas reservoirs is irreducible water saturation (Swir). The completion of oil and gas reservoir development tasks, such as fluid identification, productivity prediction, and water-flooded reservoir discrimination, requires the accurate evaluation of Swir. Nuclear magnetic resonance (NMR) logging can reflect the intricate pore structure of reservoirs, so it offers a natural advantage in the evaluation of Swir, but its high measurement cost leads to infrequent use. In geophysical logging, electrical imaging logging can obtain pore size distribution information at a lower cost. Hence, a method based on electrical imaging logging data is proposed to predict Swir. This method not only has a high degree of accuracy but is also cost-effective. First, the pore characteristics of the bound fluid were analyzed with the mercury injection capillary pressure curve. Based on the capillary pressure approximation theory, the reverse cumulative curve of the porosity spectrum was derived. And the physical meaning of its “inflection point” was clarified. Then, the resistivity of the formation containing just irreducible water was computed using the conversion between the core displacement pressure and resistivity. Finally, based on Archie's formula, the Swir at each depth of the reservoir was predicted. By using ultradeep carbonate reservoir logging data from the Yuanba gas field, the model was validated. The results demonstrated that the calculated values using this method agreed with the measured values from the cores. Compared with the core fitting method, the average absolute error is reduced by 2.61%, and the average relative error decreases by 12.0%. If NMR logging information is not present, this method serves as an effective supplement to accurately predict Swir.

Towards Large-Scale DRP Simulations: Generation of Large Super-Resolution images and Extraction of Large Pore Network Models

Representativity and accuracy of digital rock physics (DRP) simulations depend strongly on the size of the image volume and the resolution obtained. Even with one of the fastest DRP simulation techniques like pore network modelling, simulation volumes have typically been limited to few cubic millimetres for highly resolved images. In this paper, a super-resolution technique named enhanced super-resolution generative adversarial network (ESRGAN) is used to obtain well-resolved images with large field of view and to generate micro-CT images with resolution enhancement factors of × 4 and × 8. Subsets of resulting ESRGAN images were tested against the same volume (of acquisitions resolved at high and low resolution) by comparing petrophysical properties of interest. Pore network extraction and multiphase simulation results showed that pore size distribution, porosity, permeability, drainage capillary pressure and relative permeability curves obtained using ESRGAN images were more accurate. Large images, however, pose subsequent limitations on DRP simulations as pore network extraction code needs a lot of memory to process them (usually more than 60 GB of RAM for 15003 voxels image). Thus, we present a novel stitching strategy that is developed to enable the extraction of pore networks on such large images. Several validation cases of this method are presented to test the accuracy of the results from stitched networks on single- and multiphase flow properties. Finally, our stitching tool was used to generate two large networks of 3.6 million and 9.2 million elements, respectively, from two large ESRGAN images of approximately 49003 voxels.

A new surfactant wettability alteration model for reservoir simulators

AbstractSurfactants enhance oil recovery in naturally‐fractured oil‐wet rocks by wettability alteration and interfacial tension reduction. The oil‐wet state is ascribed to the adsorption of soap on the rock surface. Soaps are the dissociated forms of carboxylic acids in the crude oil, that is, carboxylate surfactants. This paper describes a new mechanistic surfactant wettability alteration model that was developed for and implemented in a reservoir simulator. The model captures the geochemical reactions of acid/soap, the formation of mixed micelles, Henry's law adsorption, and the formation of cationic surfactant‐anionic soap ion‐pairs. A new wettability scaling factor is used to interpolate between the oil‐wet and water‐wet relative permeability and capillary pressure curves. The new model also accounts for the effect of salinity and pH, so it should also be useful for modeling low‐salinity flooding without surfactant. Previous surfactant wettability alteration models ignored the underlying mechanisms and were not predictive. Simulations of both static and dynamic imbibition were performed to better understand the key surfactant parameters and the dynamics of wettability alteration, microemulsion phase behavior, and interfacial tension reduction on oil recovery. Optimizing surfactant formulations for wettability alteration is discussed.

Stress sensitivity of carbonate gas reservoirs and its microscopic mechanism

In order to evaluate the stress sensitivity of carbonate reservoirs, a series of rock stress sensitivity tests were carried out under in-situ formation temperature and stress condition. Based on the calibration of capillary pressure curve, the variable fractal dimension was introduced to establish the conversion formula between relaxation time and pore size. By using the nuclear magnetic resonance (NMR) method, the pore volume loss caused by stress sensitivity within different scales of pore throat was quantitatively analyzed, and the microscopic mechanism of stress sensitivity of carbonate gas reservoirs was clarified. The results show that fractures can significantly affect the stress sensitivity of carbonate reservoirs. With the increase of initial permeability, the stress sensitivity coefficient decreases and then increases for porous reservoirs, but increases monotonously for fractured-porous reservoirs. The pore volume loss caused by stress sensitivity mainly occurs for mesopores (0.02–0.50 μm), contributing more than 50% of the total volume loss. Single high-angle fracture contributes 9.6% of the stress sensitivity and 15.7% of the irreversible damage. The microscopic mechanism of the stress sensitivity of carbonate gas reservoirs can be concluded as fracture closure, elastic contraction of pores and plastic deformation of rock skeleton.

A novel approach for estimating pore size distribution and capillary pressure in hydrocarbon zone through hydraulic flow unit framework using NMR log

Nuclear magnetic resonance (NMR) logging imparts a wealth of information regarding the petrophysical characterization of rocks including pore size distribution and capillary pressure. However, the NMR data can only be comprehensively utilized when formation pores are fully water-saturated. As with hydrocarbon saturation increase in rock pores the NMR's transverse relaxation curve (T2 distribution) gets distorted and this in turn causes flawed measurement of petrophysical and fluid properties. Therefore, the estimation of representative pore structure and capillary pressure from hydrocarbon zone utilizing T2 distribution has traditionally been quite arduous. The previous correction methods in this regard mostly require expensive core data for their implementation, which makes them less desirable. In this study, a novel workflow has been introduced which does not necessitate expensive core data for its application. The new method employs the concept of hydraulic flow units (HFUs), which are zones within a reservoir having consistent petrophysical and geological properties to subdivide the reservoir rock while investigating the T2 distribution character variation through a statistical approach to determine the most optimally informed reconstruction of effected T2 distributions in hydrocarbon zone for accurate petrophysical characterization. After implementing the novel workflow on a carbonate reservoir having gas, the before and after comparative analysis of T2 distribution, pore size distribution (PSD) and capillary pressure curves show promising results. The novel workflow establishes a robust and cost-effective methodology for NMR T2 distribution correction in hydrocarbon zone for un-cored and partially cored wells.

Quantitative evaluation of reservoir quality of tight oil sandstones in chang 7 member of Ordos Basin

In order to establish a quantitative evaluation system for reservoir quality suitable for tight oil sandstones, in this study, taking the Chang 7 Member in the Maling area of the Ordos Basin as an example, the nuclear magnetic resonance, clay mineral analysis, high pressure mercury injection analysis and logging interpretation technology have been used to carry out a comprehensive evaluation of the pore structures, sand body structures and oil-bearing properties of tight oil sandstone reservoirs. The results show that the pseudo-capillary pressure curves transformed by the NMR T2 spectra are consistent with the capillary pressure curves measured by the core experiments. This method can be used for accurate characterization of the pore structures of the reservoir. The pore structure parameters calculated based on the pseudo-capillary pressure curves can accurately reflect the pore structures of the reservoirs such as micropores-thin throats and complex tortuosity. At the same time, the smoothness feature of conventional logging curves is used to evaluate the sand body structures and heterogeneity of the reservoir, and the apparent energy storage coefficient is introduced to quantitatively evaluate the oil-bearing properties of tight oil reservoirs. The evaluation results are in good agreement with the actual production situation. The larger the apparent energy storage coefficient, the higher the initial output of the oil wells. The evaluation results of the reservoir quality of the tight oil sandstones constructed in this paper are highly consistent with the production status, so the method has broad application prospects.

Investigation and prediction of pore type system by integrating velocity deviation log, petrographic data and mercury injection capillary pressure curves in the Fahliyan Formation, the Persian Gulf Basin

Investigation and prediction of pore type system by integrating velocity deviation log, petrographic data and mercury injection capillary pressure curves in the Fahliyan Formation, the Persian Gulf Basin

2D Surface Roughness Quantification for Enhanced Petrophysical Applications

Summary Surface roughness is an essential rock parameter affecting petrophysical properties that are surface sensitive such as characterization of pore structure and wettability. For instance, Wenzel’s contact angle formula for rough surfaces requires knowledge of the surface roughness, and surface roughness is expected to speed up the aging of cores in crude oil for wettability restoration. In addition, proper quantification of surface roughness is critical for obtaining representative, roughness-independent, pore sizes for applications such as prediction of permeability and interpretation of capillary pressure curves. Intuitively, a surface is better characterized in 2D than in 1D. This 2D study is a continuation and enhancement of the previous 1D work, recently published in the SPE Journal (Ma et al. 2021). In this current paper, a comprehensive investigation of 1D vs. 2D surface roughness measurements is conducted to evaluate and cross validate the two approaches. In this study, surface roughness is measured on 26 carbonate rock samples by laser scanning confocal microscopy (LSCM), where both the 1D absolute increment surface roughness, Sr, and the 2D interfacial area ratio of surface roughness, Sdr, are reported. As expected, the results indicate that surface roughness characterized by 2D Sdr has a greater dynamic range than the 1D Sr measurement, i.e., the 2D Sdr provides a more representative characterization of surface roughness. A detailed account of methodologies, assumptions, limitations, validation, and applications of the 1D and 2D surface roughness characterization is documented in this paper. To extract the roughness features present on rock grain surfaces, effects of de-spiking and filter length, used to eliminate pore-size effects, are investigated. For specific applications of surface roughness corrected pore-size estimation from nuclear magnetic resonance (NMR) measurements, differences in length scales of surface roughness are compared between LSCM measurement and that derived from NMR diffusion-T2 plus BET (Brunauer-Emmett-Teller) surface area. The surface roughness-corrected NMR pore-size distribution is also validated against the pore-size distribution obtained from the measurement of micro-computed tomography (CT) scanning.

Rate-Controlled Mercury Injection Experiments to Characterize Pore Space Geometry of Berea Sandstone

Interpretation of the relationship between heterogeneity and the flow in porous media is very important in increasing the recovery factor for an oil or gas reservoir. Capillarity for instance, controls fluids static distribution in a reservoir prior to production and remaining hydrocarbons after production commences. Therefore, capillary pressure data are used by petroleum engineers, geologists, and petrophysicists to evaluate production characteristics of petroleum accumulations. Conventional pressure-controlled mercury porosimetry produces an overall capillary pressure curve and pore throat size distribution data that provide little information about the porous medium structure and pore geometry. The present study provides information on three capillary pressure curves obtained from rate-controlled mercury injection porosimetry; one describes the larger pore spaces or pore bodies of a rock, another describes the smaller pores or pore throats that connect the larger pores, and a final curve which corresponds to the overall capillary pressure curve obtained from the conventional pressure-controlled mercury injection. An experimental constant-rate mercury injection apparatus was constructed that consists of a piston displacement pump, a computer controlled stepper motor drive and a core sample cell designed to minimize dead volume. The apparatus was placed in a glass chamber and subjected to an air bath to maintain a constant temperature of 27o C throughout the experiments. Then constant rate mercury injection experiments were performed on three Berea Sandstone core plugs. Results show that volume-controlled or rate-controlled porosimetry provides considerably more detailed data and information on heterogeneity and the statistical nature of pore space structure than the conventional pressure-controlled porosimetry as pressure fluctuations with time reveal menisci locations in pore bodies and pore throats. Moreover, pore size distributions based on volume-accessed pores and pore radii were obtained from the pressure versus saturation relationship.

Prediction of centrifuge capillary pressure using machine learning techniques

In current literature in the petroleum industry, machine learning has been used to predict capillary pressure only on the centrifugal data points and not the complete capillary pressure curves generated from existing correlations after analysis. This paper will present novel information that will benefit the petroleum industry as it shows machine learning techniques can be used to obtain the complete capillary pressure curve which is the end goal in undertaking an SCAL centrifuge experiment. This research involves testing core samples using a centrifuge set up to produce capillary pressure data points. Then, using a commercial SCAL interpretation software, the collected data is utilized to generate complete capillary pressure curves based on developed literature correlations. RCAL data for the core samples is also obtained to be used with the machine learning techniques. The machine learning models are then applied to the collected data to predict the capillary pressure curves. Optimization of the different machine learning techniques is done to improve the predictions. The results show the machine learning techniques perform very well on the validation set after being trained on the training set. The machine learning models also provide reasonable prediction of the complete capillary pressure curves on the testing data set. Changing of the machine learning technique parameters also shows the effect on the overall precision and the improvements that can be made. Further research can be done to see the effectiveness of using machine learning techniques to predict other SCAL properties such as relative permeability. This can then greatly reduce the time needed to obtain these extremely important properties for reservoir characterization.

Comparing Centrifuge, Steady-State and Semi-Dynamic Methods for Relative Permeability and Capillary Pressure Determination: New Insights

Relative permeability and capillary pressure are essential parameters for understanding multiphase flow in porous media and scenarios of production in oil or gas reservoirs. There are several experimental methods for determining the relative permeability curves: unsteady-state (USS), steady-state (SS), and semi-dynamic (SD) methods. Each method has advantages and weaknesses. Although the USS approach leads to fast data results, the interpretation neglects the capillary pressure effects and provides a limited amount of data points obtained after breakthrough. The SS method is time consuming but enables covering a wider range of saturation with data points if the test is well designed. The SD method may be more time consuming than the SS method but provides both relative permeability to the injected phase and capillary pressure. The relative permeability to the produced phase is then determined by numerical means. The main objective of this study was to compare the water-oil relative permeability curves obtained from the steady-state and semi-dynamic methods performed at reservoir conditions with live fluids. Carbonate core plugs of same rock type and same properties were selected for this experimental program. The samples were brought to the same irreducible water saturation at a constant brine-oil capillary pressure using a centrifuge before being dynamically aged with live oil. In addition to monitoring the average saturation using material balance (MB), a linear X-ray scanner was used for in-situ saturation monitoring (ISSM) along the core samples. The oil relative permeability from the SD method was simulated with fixed water relative permeability and capillary pressure by history-matching the oil production and the differential pressure signal. Two additional centrifuge tests on twin plug were performed in order to measure imbibition capillary pressure and oil relative permeability at pseudo-reservoir conditions. This comparative study shows that the SD method provides similar capillary pressure and oil relative permeability curves to those obtained by centrifuge methods. Even if all Kr curves are in an acceptable envelop, some differences are observed between SD and SS Kr curves: several investigative leads are given to explain this discrepancy. It is also shown that a better saturation method needs to be implemented, especially when dealing with heterogeneous rocks. While a more robust ISSM method is being tested at TOTAL, the results presented in this paper are very encouraging.

Impact of sedimentation and diagenesis on deeply buried sandy conglomerate reservoirs quality in nearshore sublacustrine fan: A case study of lower Member of the Eocene Shahejie Formation in Dongying Sag, Bohai Bay Basin (East China)

The sandy conglomerates of the lower member of Shahejie (Es4x) in the north of Dongying Sag, Bohai Bay Basin, were investigated to understand the formation mechanism of the good reservoir and controlling factors in deeply buried strata. This research is based on seismic, logging, and core data and comprehensively utilizes methods such as core description, petrographic analysis, cathodoluminescence image analysis, SEM-EDS analysis, and mercury intrusion. The sandy conglomerates are predominantly lithic arkose and litharenite. The reservoirs in the Es4x have experienced three diagenetic processes, compaction, dissolution, and cementation. Compaction remains the major factor affecting the reservoir quality, mainly in the progradation sequence, and cementation has a destructive effect on reservoirs, principally in the retrogradation sequence. The quantification of the compaction by the compaction index revealed that mechanical compaction is higher in the progradation sequence (0.68) than in the retrogradation sequences (0.59). Compaction is suppressed by carbonate cementation, but the extensive cementation significantly degrades the reservoir quality, especially in the retrogradation sequence. Dissolution of different rock fragments, feldspar, and the whole dissolution, in general, enhance the reservoir's quality in both intervals but more in the progradation sequence. Three types of reservoirs representing type I, type II, and Type III mercury intrusion capillary pressure curves were encountered in the Es4x. The braided channels in the progradation and retrogradation sets encompass the greatest reservoir quality and are characterized by type I and II reservoirs with good petrophysical properties. The preeminent reservoirs appear in the braided channels of the progradation set. The development of high-quality reservoirs is governed by the depositional subfacies, compaction, and dissolution in the Es4x. This study will contribute to comprehending the origin of the genesis mechanism of high-quality in deep sublacustrine sandy conglomerate and will help the exploration and pre-drill for favorable reservoirs in similar basins around the world.

How does capillary pressure affect the relative permeability curves of heterogeneous carbonate rocks?

The relative permeability and capillary pressure data are critically important in estimating reservoir parameters in reservoir behavior simulation and predicting its future performance. They are critically used in comprehensive studies and the preparation of development plans. Routinely in the industry, the relative permeability curves are either determined and corrected by the analytical methods (e.g., the JBN method) or history matching. In these methods, the capillary pressure effects are generally ignored. However, the fluid flow across the heterogeneous carbonate reservoir rocks is mainly controlled by the capillary effect due to their pore size distribution and the complex mixed wettability behavior. Consequently, considering both capillary and viscous impact and the other governing mechanisms in the extraction of fluid flow functions should be regarded as necessary, especially in heterogeneous media. The effect of the capillary pressure curve on the determination and correction methods of relative permeability has been rarely addressed in the literature. Moreover, in the complex behavior of the heterogeneous mixed-wet carbonate rocks, the impact of the wettability preference on the flow functions has not been frequently reported for the reservoir fluids and the modified fluids, such as in the case of IOR/EOR methods (e.g., low salinity, engineered water, and micellar methods). For this purpose, in this study, a series of capillary pressure and relative permeability tests have been performed on different carbonate plug samples. Then, the relative permeability curves of the plug samples were measured and corrected in two cases: Pc = 0 and Pc≠0 (concerning the centrifuge data), to investigate the relative permeability of both phases. The results indicated that the injection fluid and initial wettability of the rock are critically important parameters in considering the capillary pressure as a factor in the calculation and correcting of the relative permeability curves.

Obtaining capillary pressure curves from resistivity measurements in low-permeability sandstone

The increasing global demand for energy necessitates exploring and developing low-quality prospects, e.g., low-permeability reservoirs, which contain substantial hydrocarbon resources and have the potential to fill the gap in the energy markets. Typically, modeling fluid flow using reservoir simulators requires capillary pressure curves as an input. Nonetheless, laboratory capillary pressure measurements in low-permeability samples are time-consuming and challenging. On the contrary, resistivity measurements are easier to perform in the laboratory and offer a different prospect for obtaining capillary pressure curves. This paper proposes a new approach for obtaining capillary pressure curves from resistivity measurement in low-permeability sandstone using fractal theory and genetic algorithm. First, the fractal pore system is characterized as tortuous square and triangular capillaries to account for angular pores. Afterward, the drainage process is simulated to develop an innovative electrical resistivity model in fully and partially saturated porous media. Next, the genetic algorithm matches laboratory-measured resistivity data and obtains the developed model parameters. Afterward, the matched parameters are adopted in the drainage capillary pressure model to generate capillary pressure curves. The proposed model's reliability is verified by analyzing the prediction results of eighteen sandstone core samples. Furthermore, the developed model performance is compared with different models from the literature, and the results indicated its superiority in predicting capillary pressure curves.

Role of facies cycles on the mid-upper Cretaceous Bangestan Reservoir rock typing in the Zagros Basin

The principal objectives of this research were to examine the role of sedimentary cycles and tectonics in the Ahwaz Bangestan Reservoir quality, view the vertical and lateral changes of these sedimentary cycles, and identify rock typing units. There is an urgent need to understand how interpretive data are perceived among diagenetic events, sedimentary cycles, exposure surfaces, disconformities, carbonate fabric units, porosity-permeability relationship, wettability index, and relative permeability and capillary pressure vs. saturation curves. The Ahwaz Bangestan Sequence consists of Ilam and Sarvak Formations from the late Albian to Santonian Stages, in which disconformity surfaces separated the third-order sequences. Early diagenetic processes of the Bangestan sequence include meteoric dissolution and the deposit of marine cement. The meteoric diagenesis plays an essential role in the reservoir quality of these sequences and sedimentary cycles, and the burial cement process reduces the Bangestan Reservoir quality. The Bangestan sediments experience significant disconformity surfaces in the upper Cenomanian and Post-Turonian Stages. Meteoric waters affect these exposure surfaces to 50 m, increase porosity by about 15%, and have a permeability of 5 mD. With this, the results showed that there is a positive relationship between permeability and porosity data of the Bangestan sedimentary facies. In this regard, grainstone and packstone facies in the Ilam Formation demonstrated a higher reservoir quality than other facies, except for secondary chalky facies in Zone C1, where severe meteoric diagenesis occurred before lithification. Besides, the sedimentary model of the Bangestan Reservoir revealed six facies association, including tidal flat, lagoon, back shoal, rudist biostorm, shoal, and deep-marine with terrigenous layers. Given rock typing classification, four geological static rock typing (GSRT) were recognized with good correlation among lagoon, back shoal, rudist biostorm, and shoal facies association. The results demonstrated a positive relationship between permeability and porosity characteristics, leading to higher porosity and permeability in facies association of shoal and rudist biostorm with better GSRT. Besides, facies association of back shoal and lagoon with lower porosity and permeability represented worse GSRT. However, due to different diagenesis events, open-marine facies did not follow an adequate GSRT. Furthermore, three oil-wet geological dynamic rock typing (GDRT) and two water-wet GDRTs were identified, indicating the dynamic behavior of facies association. As a result, facies association with better reservoir quality (i.e., higher permeability and porosity) present higher GDRT, while facies association with worse reservoir quality (i.e., lower permeability and porosity) show lower GDRT.

Critical parameters controlling wettability in hydrogen underground storage - An analytical study

The large-scale implementation of hydrogen economy requires immense storage spaces to facilitate the periodic storage/production cycles. Extensive modelling of hydrogen transport in porous media is required to comprehend the hydrogen-induced complexities prior to storage to avoid energy loss. Wettability of hydrogen-brine-rock systems influence flow properties (e.g. capillary pressure and relative permeability curves) and the residual saturations, which are all essential for subsurface hydrogen systems. This study aims to understand which parameters critically control the contact angle for hydrogen-brine-rock systems using the surface force analysis following the DLVO theory and sensitivity analysis. Furthermore, the effect of roughness is studied using the Cassie-Baxter model. Our results reveal no considerable difference between H 2 and other gases such as N 2 . Besides, the inclusion of roughness highly affects the observed apparent contact angles, and even lead to water-repelling features. It was observed that contact angle does not vary significantly with variations of surface charge and density at high salinity, which is representative for reservoir conditions. Based on the analysis, it is speculated that the influence of roughness on contact angle becomes significant at low water saturation (i.e. high capillary pressure).

A new method of evaluating well-controlled reserves of tight gas sandstone reservoirs

Based on static geology and dynamic production of typical wells in Yan'an gas field, a convenient method of the wells controlled reserves was established combining with material balance method (MB). The method was applied to 88 wells in Yan'an tight gas field. The results show that: ①Controlled by pore structure, wells are divided into three types based on the morphology of the capillary pressure curve and the analysis of the parameter characteristics, and their productivity is evaluated, respectively. ②The flow material balance method (FMB) ignores the change of natural gas compressibility, viscosity and Z in the calculation. After the theoretical calculation of 30 gas samples, the slope of the curve of the relationship between bottom hole pressure and cumulative production and the slope of the curve of the relationship between average formation pressure and cumulative production are not equal. ③Compared with the results of the MB, the result of the FMB is smaller, and the maximum error is 34.66%. The consequence of the modified FMB is more accurate, and the average error is 2.45%, which has good applicability. The established method is simple, only requiring production data with high precision, providing a new method to evaluate well-controlled reserves of tight gas sandstone. This method with significant application value can also offer reference values for other evaluating methods of well-controlled reserves.