Tight Rocks Research Articles

Frequency-dependent P-wave anelasticity due to multiscale (fractal) heterogeneities in rocks

Understanding the effect that multiscale heterogeneities have on the wave responses of rocks at different frequencies is essential in the interpretation of seismic data. In fact, the behaviors of ultrasonic and seismic waves differ because the experiments involve different spatial scales. Then, a solution is to apply a theory that establishes a relation between the wave properties at different frequency bands considering a size range of heterogeneities. To investigate this problem, we have measured the compressional wave (P-wave) anelasticity (velocity and attenuation) of tight reservoir rocks at ultrasonic, sonic and seismic frequencies. The wave behavior as a function of porosity or clay content shows a consistent trend. With increasing confining pressure, the effect of porosity on attenuation decreases, while that of clay content gradually becomes important. To interpret the data, we propose a double-fractal poroelasticity model by incorporating the self-similarity characteristics of cracks and clay minerals. The comparison between the experimental data and model results reveals the fractality of the clay inclusions and cracks, with radii range of [10−6, 10−1.5] m and [10−6, 10−3.1] m, respectively, which is responsible for the anelastic behavior of the waves on a wide frequency band.

Analytical modification of EDFM for transient flow in tight rocks

The commercial development of unconventional resources with multiply fractured horizontal wells has been in the spotlight over the last ten years because of the significant contribution of unconventional oil and gas (UOG) reservoirs to the total US oil and gas production. UOG reservoirs contain multiscale fractures with heterogeneous properties, so the focus has been on efficient and accurate models that can account for these fractures individually. One of such models is the embedded discrete fracture model (EDFM), which has been applied to various types of fractured reservoirs. This work shows that the application of EDFM in fractured tight rocks yields significant errors because it cannot account for the expected transient flow between the matrix and fractures. To address the limitation when EDFM is used in tight rocks with structured Cartesian grids, we modified the matrix/fracture non-neighboring connection (NNC) flux in EDFM by multiplying it with a transient factor. We obtained this factor as in the transient matrix/fracture transfer term for dual-continuum models and implemented it in in our open-source shale simulator. We simulated a single vertical fracture in the middle of a tight reservoir with and without this EDFM modification and show the importance of the proposed modification. We also simulated cyclic gas enhanced oil recovery (CGEOR) in a fractured Bakken shale oil well and analyzed the model results using standard rate-transient analysis plots to evaluate the significance of the proposed modification. The results show that the standard EDFM underestimates oil and gas production by up to 73% at early times. This work presents the first analytical modification of EDFM to account for the nonlinear pressure drop expected near fracture surfaces. Comparing the modified and standard EDFM model results to a reference solution shows that the modified EDFM matches it. In contrast, the standard EDFM cannot match the reference solution when we use structured Cartesian grids with linear spacing. Additionally, by timing the simulation of a representative Bakken shale oil reservoir with 256 fractures, we show that the analytical modification proposed is only 1.5% slower than the standard EDFM.

Petrophysical characterization, BIB-SEM imaging, and permeability models of tight carbonates from the Upper Jurassic (Malm ß), SE Germany

Tight carbonate rocks are important hydrocarbon and potential geothermal reservoirs, for example, in CO2-Enhanced Geothermal Systems. We report a study of outcrop samples of tectonically undeformed tight carbonates from the upper Jurassic “Malm ß” formation in Southern Germany near the town of Simmelsdorf (38 km NE of Nuremberg) to understand bulk petrophysical properties in relation to microstructure and to compare models for permeability prediction in these samples. We applied Archimedes isopropanol immersion, Helium pycnometry, mercury injection, gamma density core logging, and gas permeability measurements, combined with microstructural investigations and liquid metal injection (LMI-BIB-SEM). In addition, ultrasonic velocity was measured to allow geomechanical comparison of stratigraphically equivalent rocks in the South German Molasse Basin (SGMB). Results show only small variations, showing that the formation is rather homogeneous with bulk porosities below 5% and argon permeabilities around 1.4E−17 m2. The presence of stylolites in some of the samples has neither a significant effect on porosity nor permeability. Pores are of submicron size with pore throats around 10 nm and connected as shown by Mercury injection and Liquid Metal injection. Samples have high dynamic Young’s Modulus of 73 ± 5 GPa as expected for lithified and diagenetically overmature limestones. Moreover, no trends in properties were observable toward the faults at meter scale, suggesting that faulting was post-diagenetic and that the matrix permeabilities were too low for intensive post-diagenetic fluid–rock interaction. Petrophysical properties are very close to those measured in the SGMB, illustrating the widespread homogeneity of these rocks and justifying the quarry as a reasonable reservoir analog. Permeability prediction models, such as the percolation theory-based Katz-Thompson Model, Poiseuille-based models, like the Winland, the Dastidar, the capillary tube, and the Kozeny-Carman Models, as well as several empirical models, namely, the Bohnsack, the Saki, and the GPPT Models, were applied. It is shown that the capillary tube Model and the Saki Model are best suited for permeability predictions from BIB-SEM and mercury injection capillary pressure results, respectively, providing a method to estimate permeability in the subsurface from drill cuttings. Matrix permeability is primarily controlled by the pore (throat) diameters rather than by the effective porosity.

Geomechanical brittleness index prediction for the Marcellus shale exploiting well-log attributes

Geomechanical brittleness of tight formations calculated from Poisson's Ratio with Young's Modulus requires laboratory testing of cores and/or estimation from shear wave acoustic logs. In shale exploitation budgets are not available to provide those measurements in many wells and it is desirable to estimate a geomechanical brittleness index (BIg) from a basic, often limited, suite of available well logs. BIg helps field operators to select the most prospective sections of tight rocks that are likely to benefit most from fracture stimulation. A machine-learning (ML) approach that combines a few recorded well logs with derivative and volatility attributes calculated from that recorded data is applied to two wellbores that penetrate the Middle Devonian formations (Appalachian Basin). This technique is novel as it has not been previously applied to predict BIg. The results demonstrate that ML models involving just two or three recorded well logs plus selected attributes as input variables provide BIg predictions that are as accurate as ML models that involve three and five recorded well logs as input variables, respectively. Moreover, the ML models involving attributes are as generalizable as ML models based only on multiple recorded well logs when applying models trained with data from one well to predict BIg from well log data in another nearby well. Extreme gradient boosting and elastic net models provide the lowest BIg prediction errors when the trained models are applied to log data from another well. Feature importance analysis identifies that the recorded compression sonic log, bulk density and gamma ray, in that order, are the most influential features in the BIg prediction models applied to the two Marcellus Shale wells. However, two of calculated well-log attributes (moving averages of the well-log derivative and volatility) are particularly effective at improving the BIg predictions when used in combination with just those three recorded well logs. The technique is worth testing in other shale basins.

Subcritical crack growth behavior of clay‐rich unconventional tight rocks under water‐saturated conditions

AbstractHydraulic fracturing is the most widely used primary method for the stimulation of unconventional oil and gas resources. While knowledge of hydraulic fracture parameters is critical to reservoir productivity, predicting the fracture initiation is important for determining the complexity of the fracture network. Subcritical crack growth in reservoir rock plays an important role in forming fracture networks, but the understanding of the influence of fracturing conditions on subcritical crack growth is still lacking. In this paper, the subcritical crack growth behavior of sandstone and shale under ambient air, deionized (DI) water, and slick‐water conditions is studied. X‐ray diffraction analysis is done on the rock samples to determine their mineralogical composition, while tensile strength is measured by the Brazilian test. Then in Load Relaxation mode, a Double‐Torsion test (DT) is carried out under different conditions to study the subcritical crack growth of the samples. To further verify the influence of clay‐rich minerals, a similar analysis is performed on clay‐free granitic rock samples. The results of the tensile strength test and DT test demonstrate that the presence of clay minerals is the main reason for the difference in the subcritical crack growth behavior of shale and sandstone samples. DI water seems to better improve the subcritical crack growth compared with other test conditions. The value of the Subcritical Index (n) is smaller in a slick‐water environment than that in a DI water environment, revealing that slick water can better promote complex fracture propagation.

Using Machine Learning to Predict Multiphase Flow through Complex Fractures

Multiphase flow properties of fractures are important in engineering applications such as hydraulic fracturing, evaluating the sealing capacity of caprocks, and the productivity of hydrocarbon-bearing tight rocks. Due to the computational requirements of high fidelity simulations, investigations of flow and transport through fractures typically rely on simplified assumptions applied to large fracture networks. These simplifications ignore the effect of pore-scale capillary phenomena and 3D realistic fracture morphology (for instance, tortuosity, contact points, and crevasses) that lead to macro-scale effective transport properties. The effect of these properties can be studied through lattice Boltzmann simulations, but they require high performance computing clusters and are generally limited in their domain size. In this work, we develop a technique to represent 3D fracture geometries and fluid distributions in 2D without losing any information. Using this innovative approach, we present a specialized machine learning model which only requires a few simulations for training but still accurately predicts fluid flow through 3D fractures. We demonstrate our technique using simulations of a water filled fracture being displaced by supercritical CO2. By generating highly efficient simulations of micro-scale multiphase flow in fractures, we hope to investigate a wide range of fracture types and generalize our method to be incorporated into larger discrete fracture network simulations.

Dependence of effective permeability on pore pressure gradient at low flow rates in low-permeability limestone

Many researchers note a nonlinearity of flow in tight rock samples at low rates. The effects include changes in apparent permeability with pore pressure gradient and so-called threshold gradients, below which low flow or no flow occurs. It is believed that these effects may be related to the influence of adhesive layers with altered properties at the interfaces between liquid and solid phases. For low-permeable rocks, the estimation of reservoir permeability without taking into account the nonlinearity of the flow can lead to significant errors. An account of the flow nonlinearity also can downgrade the reservoir productivity estimation and may result in underestimation of stationary oil zone appearances. Conventional methods for studying fluid flows in porous rocks are poorly suited for studying their permeability when approaching zero flow rates because of the lack of accuracy. Such studies also require a special approach for the interpretation of the data obtained. At the same time, there is a lack of discussion of the appropriate experimental technique in the publications known. Our goal was to develop a technique suitable for studying the flow nonlinearity at extremely low flow rates. Using the developed experimental technique, we carried out three series of consecutive tests on three similar limestone core samples. The samples were taken from the aquifer; however, their porosity and permeability are similar to the typical parameters of a tight oil reservoir. During the test series, we observed the change in the deviation from the linear Darcy’s law over a long time. We realized that in the sample with the most pronounced deviation from linear flow, there was a most significant decrease in net permeability in the entire series. We believe that our method can provide more precise evaluation of the permeability of tight rocks at the near real flow rate.

Effects of different pore shapes on the pressure and frequency dependence of velocities of oil-saturated tight sandstone

The pressure dependence of elastic parameters of rocks is mainly controlled by the geometry of the pore space. In general, the compliant-stiff pore structure model can be used to reasonably describe this pressure dependence. However, our experiment measurements revealed that for tight sandstone rock with complex pore structures, the contribution of the compressibility of the stiff pores to the elastic modulus is significant. The dual porosity is not sufficient to explain the variation of ultrasonic velocity with pressure. For this reason, we adopted a triple pore structure to divide the rock pore space into equant pores, intermediate pores and compliant pores. Our laboratory measurement and model results show that this pore space division can better describe the pressure dependence of the elastic moduli of rocks. The low-frequency stress–strain measurements show that the fluid-saturated tight sandstone has obvious dispersion in the seismic frequency band, which is primarily attributed to the squirt flow effect. In order to study the pressure and frequency dependence of the elastic moduli of tight sandstone, we retrieved the geometric parameters of the pore structure from the pressure variation of the ultrasonic velocities under dry conditions. Based on this complex pore structure and the extension of the squirt flow model, we constructed an elaborate rock physics model to explain the pressure and frequency dependence of velocity. The model does not require adjustable parameters, and all parameters are measured and calculated by the laboratory, which improves the accuracy of theoretical modelling. The modified squirt flow model can be used to describe dispersion and attenuation in a wide frequency band, and fit well with the velocity measurements in both the low-frequency range and the ultrasonic frequency range under different pressures. Therefore, this rock physics model could be applied in the extraction of pore microstructure and fluid properties provided elastic moduli or velocities can be estimated accurately.

Development of resource-saving technology for excavation of flat-lying coal seams with tight roof rocks (on the example of the Quang Ninh coal basin mines)

It is shown that the creation of the variants of resource-saving systems for the development of long-column mining is one of the main directions for improving the technological schemes for mining operations in the mines of the Kuang Nin coal basin. They provide a reduction in coal losses in the inter-column pillars and the cost of maintaining preliminary workings fixed with anchorage. The implementation of these directions is difficult (and in some cases practically impossible) when tight rocks are lying over the coal seam, prone to significant hovering in the developed space. In the Quang Ninh basin, 9-10 % of the workings are anchored, the operational losses of coal reach 30 % or more; up to 50 % of the workings are re-anchored annually. It is concluded that the real conditions for reducing coal losses and the effective use of anchor support as the main support of reusable preliminary workings are created when implementing the idea put forward at the St. Petersburg Mining University: leaving the coal pillar of increased width between the reused mine working and the developed space and its subsequent development on the same line with the stoping face simultaneously with the reclamation of the reused mine working.

Machine Learning-Based Accelerated Approaches to Infer Breakdown Pressure of Several Unconventional Rock Types.

Unconventional oil and gas reservoirs are usually classified by extremely low porosity and permeability values. The most economical way to produce hydrocarbons from such reservoirs is by creating artificially induced channels. To effectively design hydraulic fracturing jobs, accurate values of rock breakdown pressure are needed. Conducting hydraulic fracturing experiments in the laboratory is a very expensive and time-consuming process. Therefore, in this study, different machine learning (ML) models were efficiently utilized to predict the breakdown pressure of tight rocks. In the first part of the study, to measure the breakdown pressures, a comprehensive hydraulic fracturing experimental study was conducted on various rock specimens. A total of 130 experiments were conducted on different rock types such as shales, sandstone, tight carbonates, and synthetic samples. Rock mechanical properties such as Young's modulus (E), Poisson's ratio (ν), unconfined compressive strength, and indirect tensile strength (σt) were measured before conducting hydraulic fracturing tests. ML models were used to correlate the breakdown pressure of the rock as a function of fracturing experimental conditions and rock properties. In the ML model, we considered experimental conditions, including the injection rate, overburden pressures, and fracturing fluid viscosity, and rock properties including Young's modulus (E), Poisson's ratio (ν), UCS, and indirect tensile strength (σt), porosity, permeability, and bulk density. ML models include artificial neural networks (ANNs), random forests, decision trees, and the K-nearest neighbor. During training of ML models, the model hyperparameters were optimized by the grid-search optimization approach. With the optimal setting of the ML models, the breakdown pressure of the unconventional formation was predicted with an accuracy of 95%. The accuracy of all ML techniques was quite similar; however, an explicit empirical correlation from the ANN technique is proposed. The empirical correlation is the function of all input features and can be used as a standalone package in any software. The proposed methodology to predict the breakdown pressure of unconventional rocks can minimize the laboratory experimental cost of measuring fracture parameters and can be used as a quick assessment tool to evaluate the development prospect of unconventional tight rocks.

Is the widely used relation between mechanical and hydraulic apertures reliable? Viewpoints from laboratory experiments

Fluid flow through rock masses is a critical issue in rock engineering and geoscience in general, from shallow to great depths. The hydraulic aperture ( e ) of a single joint under stress is a key variable for simulating the fluid flow through rock masses. Because prediction models for the mechanical aperture ( E ) of different rock joints under different normal stresses are available, the hydraulic aperture at different depths can be readily estimated using numerous E − e relations. However, experimental hydromechanical studies frequently use the normal displacement method (ND method) for determining the mechanical aperture, for which the initial aperture needs to be “estimated”. This uncertainty can propagate to the E − e relation. In this study, we conducted high-quality laboratory measurements of mechanical/hydraulic apertures of saw-cut, polished aluminum samples, which are comparable to smooth rock joints, using the YOKO 2 system under confining stresses from 3 to 120 MPa. We measured the mechanical aperture directly from the joint volume (JV method); this method differs from the widely adopted ND method for measuring joint closure. The experimental results show that the estimation uncertainty of initial aperture, which is required for converting the joint closure curves into mechanical aperture, reduces the reliability of the existing E − e relations. Using Δ E − e relations for hydromechanical coupling analysis is suggested to avoid errors due to the initial aperture estimation based on the ND method. When the JV method is used to reduce the influence of initial aperture estimation, it is important to note that the contribution of the matrix pore volume of intact rock to the mechanical aperture measurement is not negligible even when the porosity of the matrix is less than 0.1%. Contrary, the matrix permeability of impermeable rock is negligible for laboratory measurements. Finally, neglecting the quadratic Forchheimer term leads to an underestimation of hydraulic aperture. • High-quality laboratory tests of smooth joint's hydraulic/mechanical aperture. • Initial aperture assumption affects the reliability of the widely used E − e relation. • Matrix pore volume strongly affects joint volume measurement, even for tight rocks. • Fluid flow along joints is unneglectable for low permeability rocks at great depth. • Δ E − e relation is dominated by stiffness/maximum closure ratios.

Evolution process and factors influencing the tight carbonate caprock: Ordovician Yingshan Formation from the northern slope of the Tazhong uplift, Tarim Basin, China

The tight limestone of the Yingshan Formation (Ordovician) is a local tight carbonate caprock in the Ordovician Tarim Basin. It vertically overlaps with the hydrocarbon reservoirs. The diagenesis and evolution processes affect the closure of this type of caprock, but it has been scarcely studied. This research utilized detailed laboratory experiments such as thin section study, cathodoluminescence (CL) examination, isotopic analysis (carbon, oxygen, and strontium isotopes), fluid inclusion, and the well-logging data to evaluate the evolution process and factors influencing the tight carbonate caprock of the Ordovician Yingshan Formation from the northern slope of the Tazhong uplift, Tarim Basin, China. The tight carbonate rocks of the Yingshan Formation in the study area are mainly composed of micrite and grainstone. The caprock thickness of the upper Ying 1 and the upper Ying 2 members of the Yingshan Formation are 15–44 m and 8–80 m, respectively, showing good continuity. However, the seal rocks in the other members of the Yingshan Formation are discontinuous. Low energy facies zone, vertical vadose zone, slow flow zone, and zone with weak tectonic destruction are the main areas of caprock distribution. Karstification in the epigenetic stage and cementation in the burial stage are the crucial factors affecting the evolution and distribution of carbonate seal rocks. Paleogeomorphology, phreatic surfaces, original sedimentary environment, and fault distribution influence the karstification, thus enhancing the macro heterogeneity of caprock. Cementation is controlled by buried fluids (formation water, hydrocarbons, hydrothermal fluid) and improves the micro sealing of the caprock. Multistage tectonic movements and changes in the fluid environment constantly change the sealing property of the caprock, and the reservoir and seal rock can transform each other in the process of evolution. These results suggest carbonate reservoirs evaluation can thus be enhanced by combining caprock evolution to analysis effectiveness. This research explains the mechanism of the spatial distribution of carbonate caprocks and provides the theoretical basis for carbonate reservoirs exploration.

Experimental study of permeability-hydraulic fracturing characteristics of tight rocks

Experimental study of permeability-hydraulic fracturing characteristics of tight rocks

Prediction of permeability of tight sandstones from mercury injection capillary pressure tests assisted by a machine-learning approach

Mercury injection capillary pressure analysis is a methodology for determining different petrophysical properties, including bulk density, porosity, and pore throat distribution. In this work, distinct parameters derived from mercury injection capillary pressure tests was considered for the prediction of permeability by coupling machine learning and theoretical approaches in a dataset composed of 246 tight sandstone samples. After quality checking the dataset, the feature selection was carried out by correlation analysis of different theoretical permeability models and statistical parameters with the measured permeability. Finally, porosity, median capillary pressure, Winland model, and mean pore-throat radius (corresponding to the saturation range 0.4-0.8) were chosen as the input features of the machine learning model. As the machine learning approach, a support vector machine (SVM) model with a radial basis function kernel was proposed. Furthermore, the model and its metaparameters were trained with a particle swarm optimization (PSO) algorithm to avoid over-fitting or under-fitting. In contradiction to the theoretical models, the implemented SVM-PSO model could acceptably predict the experimentally measured permeability values with an R2 rate of over 0.88 for training and testing datasets. The introduced approach could reduce the mean relative errors from about 10 to values less than 0.45. The improvements were more significant for low permeability samples. This successful implementation shows the potential of coupled usage of theoretical and machine learning methodologies for improved prediction of permeability of tight sandstone rocks. Cited as: Abbasi, J., Zhao, J., Ahmed, S., Jiao, L., Andersen, P., Cai, J. Prediction of permeability of tight sandstones from mercury injection capillary pressure tests assisted by a machine-learning approach. Capillarity, 2022, 5(5): 91-104. https://doi.org/10.46690/capi.2022.05.02

Simulation of flow characteristics and development of permeability model in fractured-vuggy carbonate reservoir

Fractured-vuggy carbonate reservoirs have complex pore structure, significant heterogeneity, and irregular permeability-porosity relation, which make existing evaluation methods unable to accurately calculate the permeability. To investigate the flow characteristics of carbonate rocks with triple-porosity, 3D digital rock models were constructed from X-ray computed tomography (CT) scanning images of carbonate cores collected in the field, and the physical properties of rocks were obtained by combining digital rock analysis (DRA) and nuclear magnetic resonance (NMR) experiment. The effects of fractures and vugs on the permeability of carbonate rocks was investigated using the Stokes-Brinkman method, and then a new fractured-vuggy carbonate permeability model was developed by artificially adding vugs and fractures. The results indicate that the carbonate pores can be divided into matrix pores, vugs, and fractures according to their sizes by combining digital rock analysis and T2 spectrums. The transport resistance is effectively reduced by fractures and vugs, which leads to the change of the flow path. For tight carbonate rocks, the dominant flow path formed through fractures is a crucial factor affecting permeability. On the contrary, unconnected vugs have less effect on permeability. Finally, the new permeability model was applied to the logging interpretation of field data. The new model is in better agreement with the permeability analysis of field cores, which greatly improves the permeability calculation accuracy of the triple-porosity reservoir in the study area.

Friction Coefficients Calculation via Surface Roughness Characterization for Tight Sedimentary Rocks

Friction Coefficients Calculation via Surface Roughness Characterization for Tight Sedimentary Rocks

An Efficient Laboratory Method to Measure Stress-Dependent Tight Rock Permeability With the Steady-State Flow Method

The matrix permeability of tight formations is important for many geological and engineering applications, such as CO2 geological sequestration, disposal of nuclear waste, and production of unconventional hydrocarbon and coalbed methane. In the case of hydrocarbon production, the reservoir permeability decreases with decreasing pore pressure or increasing effective stress. Laboratory characterization of the relationship between matrix permeability and effective stress (and pore pressure) is generally time consuming since the current methods are based on the so-called point-by-point approach that measures one permeability data point only with one test run, and the relationship is generally represented with multiple data points. In this paper, we present a method to determine matrix permeability, its relationship with effective stress, and the Biot coefficient of a tight rock sample with three steady-state flow test runs using large pressure gradients. Unlike the traditional steady-state flow method based on linear flow theories, analytical results based on a nonlinear flow theory are used for determining the related relationship and parameters. The gas properties and permeability along the core sample vary with gas pressure and effective stress, while the traditional method treats them as constants for a given test run. To get the same set of parameters, our method only requires three test runs, and each test run of our method takes a much shorter time than the traditional method because our method is based on nonlinear flow theory and thus allows for the use of large pressure gradients. Comparisons of the permeability measurements with those obtained using traditional methods and numerical simulations demonstrate that our new method can get satisfactory results.

A mathematical diffusion model of carbon isotopic reversals inside ultra-tight Longmaxi shale matrixes

Developing mathematical models for high Knudsen number (Kn) flow for isotopic gas fractionation in tight sedimentary rocks is still challenging. In this study, carbon isotopic reversals (δ13C1 > δ13C2) were found for four Longmaxi shale samples based on gas degassing experiments. Gas in shale with higher gas content exhibits larger reversal. Then, a mathematical model was developed to simulate the carbon isotopic reversals of methane and ethane. This model is based on these hypotheses: (i) diffusion flow is dominating during gas transport process; (ii) diffusion coefficients are nonlinear depending on concentration gradient. Our model not only shows a good agreement with isotopic reversals, but also well predicts gas production rates by selecting appropriate exponents m and m∗ of gas pressure gradient, where m is for 12C and m∗ is for 13C. Moreover, the (m−m∗) value has a positive correlation with fractionation level. (m1−m1∗) of methane are much higher than that of ethane. Finally, the predicted carbon isotopic reversal magnitude (δ13C1−δ13C2) exhibits a positive relationship with total gas content since gas in shale with higher gas content experiences a more extensive high Kn number diffusion flow. As a result, our model demonstrates an impressive agreement with the experimental carbon isotopic reversal data.

Spatial Characteristics and Genesis of Tight Clastic Reservoirs in Yingcheng Formation of Changling Fault Depression in the Southern Songliao Basin

Tight oil and gas has become a hot spot for unconventional oil and gas exploration. How to find high-quality reservoirs under the conditions of low porosity and permeability has become a key issue restricting tight oil and gas exploration. This paper takes the deep-seated tight clastic rocks in the Changling fault depression in the Songliao Basin as the research object and comprehensively applies various technologies and methods such as microscopic observation, temperature measurement of inclusions and paleopressure recovery, and water-rock simulation experiments, to summarize the storage of tight reservoirs. Set space types and analyze their formation mechanism. The research results show that (1) the tight clastic reservoir space types of Yingcheng Formation in the Longfengshan subsag of the Changling fault depression in the southern Songliao Basin include residual primary pores, secondary dissolved pores, and microfractures, with mainly secondary dissolved pores; (2) pore lining chlorite is an important mechanism for the preservation of primary pores; (3) water-rock simulation experiments have confirmed that volcanic rock cuttings are easy to dissolve and are the main contributor to the secondary dissolution pores in the study area; and (4) the Raman displacement technique of methane inclusions has confirmed the existence of overpressure, which is the cause of hydrocarbon generation and pressurization and is the main motivation for a microcrack formation.

Characteristics of Canister Core Desorption Gas from Unconventional Reservoirs and Applications to Improve Assessment of Hydrocarbons-in-Place

Canister core desorption has been successfully applied to coal-bed methane evaluation and exploitation as the technique eliminates the need for time-consuming down-hole fluid retrieval through flow testing. The technique has also been used for the evaluation and exploration of early-stage tight and shale gas reservoirs in recent years, although its success and applicability are poorly understood. In this study, we analyzed a comprehensive canister desorption data set on 230 core samples from nine exploration wells drilled into the Montney Formation in northeastern British Columbia part of the Western Canada Sedimentary Basin (WCSB). The purpose of the study was to illustrate the desorption characteristics of tight rocks and the relationship to reservoir properties and operational parameters. Based on the measured core properties (e.g., porosity, fluid saturation, permeability, total organic carbon (TOC) content, and adsorption isotherms) of canister samples and adjacent core samples, non-isothermal gas transport in cores was modeled to quantify the lost gas during core recovery and lost gas time at the surface. Gas volumes were measured and subsampled by canister desorption tests. The results show that the gas contents measured by on-site canister desorption only accounts for a minor (but significant) portion (about 2 to 25%) of the total gas-in-place in the Montney Formation cores, with the lower percentages being associated with samples of better reservoir qualities (e.g., higher porosity). Over 60–90% (mainly free gas) of the total gas-in-place can be lost during core recovery, and up to 10% can be lost at surface, prior to canister desorption. The measured canister desorption gas is mainly from adsorbed gas, and hence shows strong positive correlation to TOC content. The study shows that the current canister desorption test method severely underestimates in-situ gas content because it fails to correctly estimate the total lost gas content, limiting the successful application of the desorption technique. Nevertheless, the bulk properties and molecular compositions of the desorption gases are strongly correlated to those of the gases produced in the same area, exhibiting distinctive gas composition profiles throughout core desorption for different reservoir types or thermal maturity, and thus can provide invaluable information for the initial evaluation of unconventional plays. A workflow of EOS-based PVT property and compositional modeling is proposed to integrate the core desorption gas test results with core analysis data and mud gas and/or produced gas data for improved characterization of in situ reservoir fluids, and hence, better assessments of hydrocarbons-in-place and evaluations of tight and shale reservoirs.