Tight Sandstone Gas Reservoirs Research Articles

Chlorite-induced porosity evolution in multi-source tight sandstone reservoirs: A case study of the Shaximiao Formation in western Sichuan Basin

Abstract The Jurassic Shaximiao Formation in the Sichuan Basin represents a significant tight gas reservoir, exhibiting marked permeability variations between the southern and northern regions of western Sichuan. This study examines the reservoir characteristics of the Shaximiao Formation, with a focus on the evolution of sandstone porosity under bidirectional provenance conditions and the underlying causes of permeability variations. The insights derived from this research are critical for the effective exploration and development of tight sandstone gas reservoirs. Analysis of core samples and thin sections through X-ray diffraction, cathodoluminescence, scanning electron microscopy, and electron probe microanalysis reveals that the southern region predominantly consists of feldspathic and lithic sandstone, whereas the northern region is characterized by feldspathic lithic and lithic feldspathic sandstone. The average porosity and permeability in the southern region are 10.52% and 0.1334 × 10−3 μm2, respectively, while in the northern region, they are 9.74% and 0.5262 × 10−3 μm2. The primary reservoir spaces are intergranular primary pores and intragranular secondary dissolution pores. Compaction significantly reduces porosity, particularly in the northern region (23.94%) compared to the southern region (22.75%), primarily due to the presence of chlorite coatings. Cementation further reduces porosity, whereas dissolution processes enhance it, elucidating the similar porosity values but differing permeabilities between the regions.

Multiscale Pore Architecture and Its Influence on Porosity, Permeability, and Fluid Flow in Tight Gas Reservoirs of the Shihezi H8 Formation, Ordos Basin

Characterizing pore network morphology and its influence on critical reservoir properties such as porosity, permeability, and fluid flow pathways is imperative for maximizing production from tight gas sandstone reservoirs. This study integrated petrographic and pore-scale analyses to investigate diagenetic effects on the Shihezi H8 Formation, Ordos Basin, China. Sixty core plug samples spanning depositional facies from wells were analyzed using thin-section petrography, scanning electron microscopy, laser grain size analysis, mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR), and porosity–permeability measurements. Thin-section observations indicated that formation primarily comprises litharenite and sub-litharenite sandstones deposited in fluvial–deltaic environments composed primarily of quartz and feldspar grains. Diagenesis caused significant porosity reduction through initial mechanical compaction, 3–13% quartz cementation, and localized dissolution, resulting in secondary porosity of up to 5%. Three diagenetic facies were differentiated based on variations in mineralogy and diagenetic alterations. MICP classified pore networks into three reservoir types defined by mean throat radii ranging from 0.091 to 0.270 μm. NMR distinguished pore architectures as uniformly microporous, bimodally micro–mesoporous, and heterogeneously distributed multiscale pores. Larger throat radii correlated positively with higher porosity (up to 8.6%), gas porosity (10.5%), and permeability (0.1911 mD). Grain size analysis demonstrated a positive correlation between mean detrital grain diameter (>2.6 φ, 0.18 mm, (180 µm)), and significantly elevated average porosity (5–8%) compared to finer lithologies, implying depositional energy and sorting regimes. Integrating depositional features, diagenetic alterations, and multiscale pore architecture characterization quantitatively and qualitatively enhanced predictions of heterogeneity in hydrocarbon flow behavior amongst these tight reservoirs. The optimized insights from this integrated study provide a framework to guide development strategies and field appraisal methods for maximizing recovery from unconventional tight gas formations.

Experimental Study on Interlayer Interference Characteristics During Commingled Production in a Multilayer Tight Sandstone Gas Reservoir

In this study, a practical and comprehensive experimental technique has been proposed to investigate the interlayer interference characteristics in multilayer tight sandstone gas reservoirs with multi-pressure systems and different reserves. Firstly, single-layer depletion simulation experiments were conducted to measure the gas flow rate and gas extraction efficiency for each of the six layers. A series of physical simulation experiments were then conducted to monitor gas production and pressure variations in commingled multilayer production scenarios under various conditions. Finally, interlayer interference characteristics and gas extraction efficiencies and the main controlling factors were evaluated, analyzed, and identified. The interlayer pressure differential is found to be the primary factor dictating both interference and gas production, followed by initial gas production rates, and permeability variations in the order of positive significance. A higher interlayer pressure differential, a lower initial gas production rate, and a larger permeability variation result in an increase in interlayer interference and a reduction in gas production during commingled production. Increasing the number of commingled layers leads to an overall increase in gas production losses of 10.95% for two layers to 13.35% for four layers. Layers exhibiting small interlayer pressure difference are positively compatible for commingled production.

Experimental study on the dynamic threshold pressure gradient of high water-bearing tight sandstone gas reservoir

Tight sandstone water-bearing gas reservoirs typically exhibit low porosity and low permeability, with reservoir rocks characterized by complex pore structures, often featuring micron-scale or smaller pore throats. This intricate reservoir structure significantly restricts fluid flow within the reservoir, necessitating a certain threshold pressure gradient (TPG) to be overcome before flow can commence. This study focuses on the Ordos Basin and explores the influence of high water content tight sandstone gas reservoirs on TPG under different water saturation and formation pressure conditions through experiments. A mathematical model of TPG is established using multiple linear regression method. The results show that TPG is primarily affected by water saturation, followed by formation pressure. As the water saturation increases, the TPG of the core decreases, and the change becomes more pronounced when the water saturation exceeds 50%. As formation pressure increases, the weakening of the slippage effect in gas molecules leads to TPG stabilization, especially when local pressure exceeds 25.0 MPa. The research also shows that low-permeability cores exhibit greater TPG variation with pressure changes, while high-permeability cores remain more stable. A mathematical model was developed and validated to predict TPG based on permeability, water saturation, and formation pressure. These findings highlight the need to monitor formation water content during tight sandstone gas reservoir development to optimize production strategies, providing valuable insights for improving reservoir management and guiding future research.

Current Status of Research on Seepage Mechanism in Tight Sandstone Gas Reservoirs

China's tight sandstone gas reservoirs have a large amount of resources, which is an important part of future energy. At present, one of the main problems facing the production of tight sandstone gas reservoirs is water production, and the water production of gas wells is a key influence factor restricting the stable and increased production of gas reservoirs. Firstly, the research status of reservoir characteristics of tight sandstone gas reservoirs is summarized, then the seepage mechanism of tight sandstone gas reservoirs is analyzed, and finally the relationship between gas and water in tight sandstone gas reservoirs is reviewed, which provides a basis for further research on the seepage mechanism of tight sandstone gas reservoirs and the law of gas and water production.

Application of vertical seismic profile multi-component data to tight sandstone gas reservoirs

Abstract Given the complex geological characteristics of the tight gas sandstone in the Shaximiao Formation of the Jurassic in the central Sichuan Basin, including its wide distribution, narrow width, and thin thickness, conventional surface seismic methods face significant challenges in reservoir delineation. To address this challenge, a vertical seismic profile (VSP) survey was conducted in the region in 2022, along with the simultaneous collection of 3D3C surface seismic data. This article mainly elaborates on a case study of using multi-component VSP technology to delineate tight sandstone gas reservoirs. By comparing the processed VSP imaging volume with the surface seismic imaging volume, it was discovered that the frequency width of the VSP image was 8 to 12 Hz higher than that of the surface seismic image. Utilizing the multi-component information in VSP data, it is feasible to more precisely delineate tight gas sandstones, thereby reducing the uncertainty of data interpretation. Based on the conventional data interpretation of these images, an innovative application suggests using the centroid frequency ratio of PSv to PP waves as an indicator for tight sandstone. The results show that this attribute has high sensitivity to this type of reservoir. Combining geological, drilling, and logging data, an interpretation template was established based on VSP data to interpret 3D3C surface seismic data and propose new drilling well locations. The conclusion is that the successful application of VSP technology cannot be achieved without the integration of multiple disciplines. The combined exploration technology of multi-component VSP and 3D3C surface seismic has been demonstrated to have high application value through practical application, significantly improving the success rate of gas wells and providing effective support for the exploration and development of tight sandstone gas reservoirs.

Study on the Percolation Law of Tight Gas in the Western Sulige Area based on the Lattice Boltzmann method

Abstract To address the problem of unable to determine the percolation law of tight sandstone gas reservoirs under laboratory conditions, especially when there are no water production measurements and no obvious edge and bottom water. In this study, takes the Western Sulige area as the research object, and based on the geological characteristics of the Western Sulige area and the lattice Boltzmann method, establishes a LB mechanism model for tight gsa in the Western Sulige area, identify Identify fluid distribution and percolation rules in the pore throat structure of Western Sulige area The results show that There are four types of bound water in the pore throats of the western Sulige area, including trapped water, bind pore water, dead pore water, and liquid film.. The remaining gas in the production process is mainly distributed in the pore throat structure, including bind pore gas, fine throat pore gas, and water seal gas. In the early stage of gas-water production, formation water mainly in the form of liquid film reduces the cross-section of natural gas flow. Subsequently, formation water mainly in the form of liquid droplets clogs the throat, thereby reducing the gas percolation capacity. Due to the capillary suction effect, liquid–solid viscous forces, and pore–throat structures, the reservoirs of Western Sulige Area is prone to water lock damage, resulting in reduced production and even production suspension of gas wells. Therefore hydraulic fracturing is a necessary measure for the development of tight gas, but the increase in the intensity of fracturing operations has increased the width of fractures and strengthened the water lock phenomenon, further worsening the percolation capacity of the matrix.

Differential controlling on the deep tight sandstone reservoirs: Insight from the second member of lower Triassic Xujiahe Formation in Xinchang area, western Sichuan basin, China

With advancements in deep exploration, the deep tight sandstone gas reservoir has become a significant exploration field. However, it remains challenging to develop on a large scale due to the unclear distribution of relatively high-quality reservoirs. In this paper, the petrology, reservoir properties, diagenesis, and structural fracturing of deep tight sandstone reservoirs are systematically studied, focusing on the second member of the Upper Triassic Xujiahe Formation (T3x2) in the Xinchang area, and the types of relatively high-quality reservoirs and their differential controlling are further clarified. According to the matching relationship between pores and fractures, tight sandstone reservoirs can be classified into four types: extremely tight, fractured, porous, and pore-fractured types. Among these, the porous and pore-fractured types are considered effective reservoirs. The formation of tight sandstone reservoirs is closely related to sedimentary microfacies, grain size, diagenesis and tectonic fracturing, with distinct controlling differences across reservoir types. Overall, sedimentary microfacies provide the foundation, while differential diagenesis and tectonic fracturing are the key factors influencing reservoir quality. Among them, the extremely tight sandstone reservoirs can form in various sedimentary microfacies, particularly in medium to fine, lithic-rich sandstones, where strong compaction and cementation are the main factors for the underdevelopment of reservoir space. In contrast, fractured reservoirs mainly form based on porous reservoirs through the superimposition of tectonic fracturing. The porous reservoirs are typically found in relatively high-energy environments such as distributary channels and mouth bars, with medium to coarse feldspar-rich sandstone. Dissolution and chlorite-liner cementation are the key factors for their pore formation. Similarly, pore-fractured reservoirs originate from porous reservoirs that have been further altered by superimposing tectonic fracturing.

Estimating pore pressure in tight sandstone gas reservoirs: A comprehensive approach integrating rock physics models and deep neural networks

Pore pressure serves as an important driving power for subsurface fluid migration and therefore has a significant impact on gas accumulation and enrichment in tight sandstone reservoirs. Tight gas is typically produced in overpressure regions, where pressure coefficients are notably elevated. Thus, it is crucial to establish an effective methodology for precise pore pressure estimation. This study introduces an approach to improve pore pressure prediction by incorporating rock physical modeling and deep neural networks (DNNs) into the classical Eaton method. Compared to conventional techniques relying on empirical correlations between pressure coefficients and elastic properties, the proposed method considers the influence of porosity, fluids, and lithology, which could enhance reliability in pore pressure prediction. Meanwhile, a prediction model is developed using logging data and DNNs to estimate mineralogical volumetric fractions based on elastic properties. This prediction model allows improved estimation of rock matrix elastic properties using seismic-inverted data, which is crucial for estimating normal compaction velocity to extend pore pressure prediction from individual boreholes to the whole study area. Real data applications demonstrate that the predicted pressure coefficients derived from seismic data using the method presented in this paper align well with the gas enrichment estimated in previous studies for the tight sandstone reservoirs. Furthermore, regions with high values of pressure coefficients correspond to high gas content. These findings validate the effectiveness of the proposed methodology, which can provide valuable insights for identifying potential tight sandstone reservoirs.

Refractured Well Hydraulic Fractures Optimization in Tight Sandstone Gas Reservoirs: Application in Linxing Gas Field

Poorly producing wells in sandstone gas reservoirs are often refractured to enhance production. Considering the mutual interference of initial/refractured fractures, conductivity dynamic evolution, non-uniform inflow, and variable mass flow in the fracture comprehensively, a semi-analytical reservoir-fracture coupled production model fusing spatial and time separation methods is introduced to model refractured well performance. The proposed model is verified by CMG. The field applications indicate that the refracture job should be carried out when production is lower than the desired value. Restoring the Cf-ini and constructing the Cf-ref can increase productivity, which increases over 8 D•cm. The production growth rate just obtained a slight improvement. The production increased significantly with Lf-ini increasing from 120~270 m and Lf-ref increasing from 100~150 m. Hence, it is essential to extend the Lf-ini under engineering conditions. The ks/km = 10 can obviously increase production, but further enlarging ks does not contribute to well performance. Conversely, further producing larger bs is vital to enhancing production. Subsequently, the optimal parameter combinations (ds > Lf-ini > Lf-ref > Cf-ini > ks > Cf-ref) for well(X1) are carried out by orthogonal experiments. This work proposes a novel method to simulate refractured vertical well performance in tight gas reservoirs for refracture optimization.

Feasibility of CO2 storage and enhanced gas recovery in depleted tight sandstone gas reservoirs within multi-stage fracturing horizontal wells

Injecting CO2 when the gas reservoir of tight sandstone is depleted can achieve the dual purposes of greenhouse gas storage and enhanced gas recovery (CS-EGR). To evaluate the feasibility of CO2 injection to enhance gas recovery and understand the production mechanism, a numerical simulation model of CS-EGR in multi-stage fracturing horizontal wells is established. The behavior of gas production and CO2 sequestration is then analyzed through numerical simulation, and the impact of fracture parameters on production performance is examined. Simulation results show that the production rate increases significantly and a large amount of CO2 is stored in the reservoir, proving the technical potential. However, hydraulic fractures accelerate CO2 breakthrough, resulting in lower gas recovery and lower CO2 storage than in gas reservoirs without fracturing. Increasing the length of hydraulic fractures can significantly increase CH4 production, but CO2 breakthrough will advance. Staggered and spaced perforation of hydraulic fractures in injection wells and production wells changes the fluid flow path, which can delay CO2 breakthrough and benefit production efficiency. The fracture network of massive hydraulic fracturing has a positive effect on the CS-EGR. As a result, CH4 production, gas recovery, and CO2 storage increase with the increase in stimulated reservoir volume.

Complementary testing and machine learning techniques for the characterization and prediction of middle Permian tight gas sandstone reservoir quality in the northeastern Ordos Basin, China

In this study, an integrated approach for diagenetic facies classification, reservoir quality analysis and quantitative wireline log prediction of tight gas sandstones (TGSs) is introduced utilizing a combination of fit-for-purpose complementary testing and machine learning techniques. The integrated approach is specialized for the middle Permian Shihezi Formation TGSs in the northeastern Ordos Basin, where operators often face significant drilling uncertainty and increased exploration risks due to low porosities and micro-Darcy range permeabilities. In this study, detrital compositions and diagenetic minerals and their pore type assemblages were analyzed using optical light microscopy, cathodoluminescence, standard scanning electron microscopy, and X-ray diffraction. Different types of diagenetic facies were delineated on this basis to capture the characteristic rock properties of the TGSs in the target formation. A combination of He porosity and permeability measurements, mercury intrusion capillary pressure and nuclear magnetic resonance data was used to analyze the mechanism of heterogeneous TGS reservoirs. We found that the type, size and proportion of pores considerably varied between diagenetic facies due to differences in the initial depositional attributes and subsequent diagenetic alterations; these differences affected the size, distribution and connectivity of the pore network and varied the reservoir quality. Five types of diagenetic facies were classified: (ⅰ) grain-coating facies, which have minimal ductile grains, chlorite coatings that inhibit quartz overgrowths, large intergranular pores that dominate the pore network, the best pore structure and the greatest reservoir quality; (ⅱ) quartz-cemented facies, which exhibit strong quartz overgrowths, intergranular porosity and a pore size decrease, resulting in the deterioration of the pore structure and reservoir quality; (ⅲ) mixed-cemented facies, in which the cementation of various authigenic minerals increases the micropores, resulting in a poor pore structure and reservoir quality; (ⅳ) carbonate-cemented facies and (ⅴ) tightly compacted facies, in which the intergranular pores are filled with carbonate cement and ductile grains; thus, the pore network mainly consists of micropores with small pore throat sizes, and the pore structure and reservoir quality are the worst. The grain-coating facies with the best reservoir properties are more likely to have high gas productivity and are the primary targets for exploration and development. The diagenetic facies were then translated into wireline log expressions (conventional and NMR logging). Finally, a wireline log quantitative prediction model of TGSs using convolutional neural network machine learning algorithms was established to successfully classify the different diagenetic facies.

Deep-learning-based natural fracture identification method through seismic multi-attribute data: a case study from the Bozi-Dabei area of the Kuqa Basin, China

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

Analysis of Factors Influencing Tight Sandstone Gas Production and Identification of Favorable Gas Layers in the Shan 23 Sub-Member of the Daning-Jixian Block, Eastern Ordos Basin

The Daning-Jixian Block harbors abundant tight sandstone gas resources. However, significant variations in gas production exist among the different wells within the block. A comprehensive study was conducted on key factors such as sedimentary strata and petrophysical characteristics to elucidate their impact on gas reservoir productivity. Linear regression equations were employed to classify the favorable reservoirs within the study area. The analysis revealed that within the first 6 months of production from the Shan 23 gas layer, daily gas production ranged from 2576.19 to 156,078.17 m3/d, averaging 24,037.9 m3/d. Over the first year, average daily production varied from 2185.05 to 136,806.99 m3/d, averaging 23,469.23 m3/d, indicating relatively stable production from the Shan 23 layer alone. In the dominant central area of the underwater distributary channel delta front in Shan23, the sand body exhibits a superimposed cutting type, resulting in high production rates. Conversely, the sand bodies on the periphery gradually transition to superimposed and isolated types, leading to decreased production. Through a correlation analysis of gas layer thickness, porosity, permeability, and initial gas well production, it was determined that gas production from the wells within the same layer is primarily influenced by gas layer thickness, porosity, and permeability. Gas saturation demonstrates a minimal impact on production according to single-factor analysis. The evaluated factors such as the gas productivity coefficient, energy storage coefficient, and enrichment coefficient exhibited similar distribution patterns across the study area. The high-value areas for the gas productivity coefficient, energy storage coefficient, and enrichment coefficient are concentrated in distributary channel zones and delta lobes. In contrast, regions with underdeveloped skeletal sand bodies generally display lower values for these parameters. The linear relationships between these parameters and the average gas production were calculated to further classify the favorable reservoirs in the study area. This study aimed to establish a scientific basis for the efficient development of the tight sandstone gas reservoirs within the Daning-Jixian Block.

Efficient development technology of Upper Paleozoic Lower Shihezi tight sandstone gas reservoir in northeastern Ordos Basin

Abstract The Lower Shihezi Formation of the Upper Paleozoic at the northeastern margin of the Ordos Basin develops widely distributed thick massive and multilayer gas reservoirs. How to formulate an effective development policy is a difficult and hot spot. In this article, reservoir characteristics and production capacity influencing factors of the tight gas sandstone in Lower Shihezi Formation in this area are systematically studied, and optimization schemes of development measures for massive and multilayer gas reservoirs are proposed. The results show that the petrophysical characteristics of the small pore–mesopore type gas reservoir in the target layer are the best, with the average porosity, permeability, and coordination number of 7.6%, 0.74 mD, and 3.3, respectively. Thick sand body, high structural position, good petrophysical properties, and high drilling rate of sandstone are all conducive to drilling high production gas wells. Development policies for massive and multilayer gas reservoirs have been formulated: (1) the preferred well type for massive gas reservoir is vertical well + horizontal well, while the preferred well type for multilayer gas reservoir is horizontal well + stepped horizontal well; (2) the reasonable horizontal segment length of massive gas reservoir is 1,000 m, and the reasonable horizontal segment length of multilayer gas reservoir is 1,250 m; (3) similar to massive and multilayer gas reservoirs, the more the fracture stages, the higher the cumulative gas production, and the optimal fracture stage number of both gas reservoirs is 8; (4) the optimal fracture half-length and the angle between the fracture and the horizontal section are 140 m and 90°, respectively; and (5) the reasonable well spacing of vertical wells is 600 m and that of horizontal wells is 750 m. The development policy proposed in this study is suitable for the efficient development of complex tight sandstone gas reservoirs in similar areas.

Accurate identification of low-resistivity gas layer in tight sandstone gas reservoirs based on optimizable neural networks

In tight sandstone reservoirs, low resistivity gas reservoirs have a certain gas production capacity, but their reservoir resistivity value is less than 20 Ω m, or their ratio to water layer resistivity is less than 2. Therefore, the identification of low resistivity gas reservoirs is a prominent problem that needs to be resolved. In this paper, on the basis of traditional experimental analysis, NMR experiments and wettability experiments were conducted. The high bound water saturation and pore fractal dimension have a significant impact on reservoir resistivity. After various experimental analysis results were preprocessed by the image pool and data pool, an optimized neural network (ONN) classification model was established based on deep learning theory. The confusion matrix result (training datasets) was 87.13%, and the ROC area of low resistivity gas layers was close to 1, indicating good recognition performance for low resistivity gas layers. The model was used to identify the properties of the J4 well reservoir section. The identification result was consistent with the actual logging resistivity values (low resistivity) and testing conclusions (gas layer). This model can accurately identify low resistivity gas reservoirs in the research area, and has important guiding significance for identifying the reservoir properties of tight sandstone gas reservoirs in the Sichuan Basin. It can provide reference value for the exploration and development of similar gas reservoirs in other regions.

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: a case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: a case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

Application of multicomponent seismic data to tight gas reservoir characterization: A case study in the Sichuan Basin, China

Combining PP and PS waves from multicomponent data is an effective hydrocarbon characterization strategy because these two wave types are sensitive to different subsurface properties. We develop a case study using multicomponent data to characterize tight sandstone gas reservoirs in the Jurassic Shaximiao Formation, the western Sichuan Basin, China. In the study area, with PP data it is difficult to distinguish sandstones, mudstones, and gas sand, whereas recently acquired multicomponent data indicate potential for the joint characterization of lithology, porosity, and gas saturation from the combination of PP and PS reflections. Sandstones and mudstones have small P-wave velocity contrasts and large S-wave velocity contrasts. Thus, PS data provide a more accurate description of sandstones, as a substantial proportion of sandstones are undetectable from PP sections. P impedance is sensitive to sandstone porosity variation, and seismic-predicted porosities based on impedance inversion are in good agreement with log-interpreted porosities. The ratio of P-wave velocity to S-wave velocity is sensitive to gas accumulation, and the ratios derived from joint PP-PS prestack inversion are determined to be better than from PP prestack inversion in terms of their agreements with logs and distinct gas-sand boundaries.

Accumulation mechanism of multi-type unconventional oil and gas reservoirs in Northern China: Taking Hari Sag of the Yin’e Basin as an example

Abstract Many multi-types of unconventional oil and gas reservoirs have been found in some faulted basins in northern China, showing good exploration potential. However, the hydrocarbon accumulation mechanism in these areas is still unclear, which limits the understanding of the distribution of oil and gas. In this study, we took Hari Sag in Yin’e Basin as an example, conducted a systematic analysis on various types unconventional oil and gas reservoirs, and revealed its characteristics and accumulation mechanisms. The study showed that there were many types of unconventional oil and gas reservoirs in Hari Sag, such as biogas reservoirs, shale gas reservoirs, shale oil reservoirs, tight sandstone oil reservoirs, tight sandstone gas reservoirs, and volcanic gas reservoirs. These reservoirs generally had characteristics of “near/within source rocks accumulation,” “coexistence of oil reservoirs and gas reservoirs,” “shallow oil and deep gas,” and so on. Research on the mechanism of hydrocarbon accumulation showed that: the lack of effective hydrocarbon migration pathway was the main reason for “near/within source rocks accumulation” of oil and gas reservoirs; the differences in the thermal evolution degree of the main source rocks at different structural positions in the sag made the distribution characteristics of hydrocarbon as “coexistence of oil reservoirs and gas reservoirs” and “shallow oil and deep gas”; and the joint development of multi-type effective unconventional reservoirs created the situation of “coexistence of multi-type unconventional oil and gas reservoirs.” It is predicted that six types of unconventional oil and gas reservoirs have a cumulative area of 381 km2, indicating that the Hari Sag has great potential for unconventional oil and gas exploration. The research results can not only guide the unconventional oil and gas exploration in Hari Sag but also provide a theoretical basis for exploration research in similar blocks.

Gas prediction in tight sandstones based on the rock-physics-derived seismic amplitude variation versus offset method

Estimating gas enrichments is a key objective in exploring sweet spots within tight sandstone gas reservoirs. However, the low sensitivity of elastic parameters to gas saturations in such formations makes it a significant challenge to reliably estimate gas enrichments using seismic methods. Through rock physical modeling and reservoir parameter analyses conducted in this study, a more suitable indicator for estimating gas enrichment, termed the gas content indicator, has been proposed. This indicator is formulated based on effective fluid bulk modulus and shear modulus and demonstrates a clear positive correlation with gas content in tight sandstones. Moreover, a new seismic amplitude variation versus offset (AVO) equation is derived to directly extract reservoir properties, such as the gas content indicator and porosity, from prestack seismic data. The accuracy of this proposed AVO equation is validated through comparison with the exact solutions provided by the Zoeppritz equation. To ensure reliable estimations of reservoir properties from partial angle-stacked seismic data, the proposed AVO equation is reformulated within the elastic impedance inversion framework. The estimated gas content indicator and porosity exhibit favorable agreement with logging data, suggesting that the obtained results are suitable for reliable predictions of tight sandstones with high gas enrichments. Furthermore, the proposed methods have the potential to stimulate the advancement of other suitable inversion techniques for directly estimating reservoir properties from seismic data across various petroleum resources.