Volcanic Reservoirs Research Articles

Characteristics of Carboniferous Volcanic Reservoirs in Beisantai Oilfield, Junggar Basin

In recent years, petroleum exploration in the Carboniferous volcanic rock reservoirs in the Junggar Basin has been the focus of important petroleum energy development in western China. The lithologic identification of volcanic rock reservoirs seriously restricts the accuracy of reservoir prediction and affects the success rate of oil exploration. Different types of volcanic rocks have different petrological characteristics and mineral assemblages, especially affected by the depositional environment. The volcanic rocks in different regions have their own uniqueness. This paper takes the Carboniferous volcanic reservoirs in Xiquan block, Beisantai Oilfield, Junggar Basin as the research target. Through a large number of core observations, casting slices, scanning electron microscopy, and X-ray diffraction methods, the Carboniferous volcanic rocks are analyzed. The petrology, pore characteristics, physical properties, and diagenetic evolution history of the reservoir are analyzed. The study shows that the volcanic facies in the Xiquan block can be divided into explosive facies, overflow facies, and volcanic sedimentary facies, among which the explosive facies is subdivided into empty subfacies (volcanic breccia-breccia tuff combination) and thermal base wave subfacies (tuff). The lithology of the reservoir is pyroclastic rock and volcanic lava, belonging to medium-porous and ultralow permeability reservoirs, and the storage space can be divided into three types: primary pores, secondary pores, and fractures. The lithology of key exploration is breccia tuff, followed by breccia tuff and volcanic breccia.

Hydraulic, acid, and proppant-carrying acid fracturing stimulation of volcanic reservoirs in Sichuan Basin, China: an experimental study

Nowadays, volcanic reservoirs show great development potential. However, the stimulation mechanism of volcanic reservoir is yet unclear. In this article, hydraulic fracturing, acid fracturing, and proppant-carrying acid fracturing of volcanic rock were analyzed by the laboratory tests. The average acid etching and proppant-embedded depths were assessed. The effect of different proppant sizes and acid types on fracture conductivity was studied. The results indicate that acid fracturing is failed to produce high-conductivity fractures. Large-sized proppants had larger embedded depths. For the hydraulic fracturing, the average depth of the 30/50 mesh proppant (5 kg/m2, 60 MPa) embedded in the volcanic rock is 33 μm, and the conductivity is 45.27 D·cm, which is 1.5 times that of the 40/70 mesh proppant. Embedded depth of proppant in the proppant-carrying acid fracturing (347 μm) was ten times larger than that in hydraulic fracturing (33 μm), but in terms of conductivity, hydraulic fracturing is only 20% better than proppant-carrying acid fracturing. This study is helpful to elucidate the mechanism of different stimulation methods and provide scientific means for the efficient development of volcanic reservoirs. Highlights In this article, experimental study is made on the stimulation mode of volcanic reservoir. There are few studies on volcanic. This study is helpful to elucidate the mechanism of different stimulation methods and provide scientific means for the efficient development of volcanic reservoirs. Based on the three-dimensional (3D) surface data of the rock, the average acid etching depth and the average embedding depth of proppant are accurately calculated by a new method. The experimental results can provide a good basis for the selection of volcanic reservoir stimulation. The embedded depth and etching depth have an intuitive image display.

Lithologic classification of pyroclastic rocks: A case study for the third member of the Huoshiling Formation, Dehui fault depression, Songliao Basin, NE China

With the ongoing discovery of volcanic oil and gas reservoirs, pyroclastic rocks have begun to attract widespread attention from both the academic and industrial sectors. Because there is more information about the cementation mode and the grain size in the Chinese classification system for pyroclastic rocks than there is in the system used throughout the rest of the world, we use the Chinese classification system to investigate the lithologies of the pyroclastic rocks in our study area. The three cementation modes dictate the three classes of pyroclastic rock: pyroclastic lava, normal pyroclastic rock, and sedimentary pyroclastic rock. Within these three modes, pyroclastic rocks are further classified by their clastic material grain size into agglomerate, breccia, and tuff. If the pyroclastic material is moved by aeolian transport, it tends to follow the positive sedimentation cycle sequence. In this study, we classify the pyroclastic rocks from the third member of the Huoshiling Formation (Fm) in the Dehui fault depression in the southern Songliao Basin. Draw the cross plots of pyroclastic lava, normal pyroclastic rock and sedimentary pyroclastic rock in the study area. Based on core date, fullbore micro-resistivity images (FMIs), and thin section analyses, we determine the mineral composition, particle size, and cementation mode of breccia bearing tuff lava, tuff lava, breccia bearing welded tuff, volcanic breccia, breccia bearing tuff, tuff, sedimentary volcanic breccia, and sedimentary tuff. Our results indicate that the decision tree method does not require all of the input curves to identify a given sample's lithology. We also found that adding more data to a support vector machine (SVM) does not necessarily translate into more accurate classification results. This classification is undertaken using two different techniques: a combination of elemental capture spectroscopy (ECS) cross plots and FMI and a SVM learning algorithm with information derived from node information in a decision tree. Ultimately, the results produced by the SVM algorithm are more accurate (recognition accuracy of 98.6%) than those generated by the ECS/FMI approach. Furthermore, the SVM algorithm requires less data and operates very efficiently. Using data from multiple wells allows for better and more rapid identification of the lithology type in the target layer; large observational or training datasets provide a strong foundation for further reservoir evaluation.

The reservoir property modeling of volcanic reservoir: An application to the Shahejie Formation, Zaoyuan oilfield, eastern China

As an increasing number of volcanic reservoirs has been discovered all over the world, the study of volcanic reservoirs has caught more attention. However, researchers mainly focus on the characterization of the external architecture of volcanic rock mass and the superimposed relationship between the rock mass, while paying little attention to the fine anatomy of the internal structure of the rock mass, making it difficult to effectively guide the development of the volcanic reservoir. Taking Zao35 block in Huanghua depression, Bohai Bay Basin, China, as an example, we find a workflow of establishing a high-resolution volcanic stratigraphic structure model and reservoir properties models by integrating well- and seismic-data analysis. The seismic data indicate that the volcanic activities consist of three stages: Stages I and III have positive seismic amplitude reflections, whereas stage II has a negative seismic reflection. The well data indicate that the lithology column of target formation in our study area consists of eight volcanic strata and seven mudstone strata. According to the lithology interpreted using well data, stages III, II, and I consist of five, one, and two volcanic eruption periods, respectively. We have established a structure and stratigraphy model with eight zones of volcanic rock and seven zones of mudstone barrier (15 zones in total) to effectively distinguish volcanic rocks (products of the eruption period) from sedimentary rocks (products of the volcanic dormant period). Based on the seismic attribute analysis, we have combined the sequential indicator simulation and local anisotropy from the seismic amplitude attribute. The model of volcanism can be reproduced by sequential indication simulation of local variogram with variable range directions. Based on the principle of “facies control” (perform lithology simulation in different regions according to lithofacies), we have used the sequential indication method to simulate volcanic rocks. The simulation results have a very good agreement with the shape of lava flows spreading around the crater. To describe the internal structure of the volcanic rock body, reveal internal lithology distribution characteristics, and reservoir physical properties, we provide an effective research method for the development of volcanic reservoir geologic research.

The Hydrocarbon Potential of Carboniferous Reservoirs in the Jimsar Sag, Northwest China: Implications for a Giant Volcanic-Petroleum Reserves

As an unconventional petroleum reservoir, the volcanic reservoir is essential for finding large-scale oil and gas reserves in deep sedimentary basins. Based on basin modeling, organic geochemistry, and organic petrology, this study evaluates the exploration potential of the Carboniferous volcanic-petroleum system in the Jimsar Sag of the southeastern Junggar Basin. The Carboniferous source rocks in the study area were developed in the Lower Carboniferous Songkharsu Formation, a set of marine–terrigenous transitional source rocks, lithologically composed of carbonaceous mudstone, mudstone, and coal. The kerogen is characterized by type II2–III, indicating a gas-prone source rock. Carbonaceous mudstones, mudstone, and coal are classified as medium–good, medium, and poor source rocks, respectively. The hydrocarbon-generating potential is close to that of the Kelameili gas field. The Carboniferous-reservoir oil in well J15 is characterized by 13C-enriched stable carbon isotopes, relatively high ƩC31–35/C30 and Pr/Ph ratios, relatively low density, gammacerane index, regular C29-sterane content, and undetected β-carotene, indicating a Songkharsu origin. The Carboniferous-reservoired gas from well J3301 has stable carbon isotope composition enriched in 13C, similar to the gas from the Kelameili gas field, and should be from the Songkharsu source rock. This set of source rocks is widely distributed in the Jimsar Sag with considerable thickness, among which thickness >100 m reaches 580 km2, accounting for 38.7% of the whole sag. The Songkharsu source rocks entered the main oil-generating window at the end of the Early Jurassic. The area of Songkharsu source rocks in the Jimsar Sag with gas-generating intensity greater than 20 × 108 m3/km2 reaches 1,015 km2, whereas that with oil-generating intensity greater than 500 × 104 t/km2 reaches 1,146 km2. However, 13 Carboniferous volcanic lithological traps were found in the sag, covering an area of 230 km2. The Carboniferous volcanic-petroleum system in the Jimsar Sag has the resource potential to form large and medium oil and gas fields, which could become a critical replacement field for volcanic oil and gas exploration in the Junggar Basin after the Klameili gas field.

Quantitative characterization of fracture-pore distribution and effects on production capacity of weathered volcanic crust reservoirs: Insights from volcanic gas reservoirs of the Dixi area, Junggar Basin, Western China

Igneous hydrocarbon reservoirs worldwide are of significant importance to the petroleum industry for oil and gas exploration. The Carboniferous weathered volcanic crust reservoirs of the Dinan salient in the northern Junggar Basin are major exploration targets of PetroChina. The present study analyzes the geological, well logging, and production data to formulate development and distribution methods for quantitative characterization of weathered volcanic crust fractures and examine their fracture-pore distributions. The effects of the fracture-pore distribution on the productivity of various lithologies of weathered volcanic crust reservoirs were investigated. Various volcanic lithofacies demonstrate the lithological differences in their physical properties, fracture development, and distributions due to the conspicuous variations in weathering resistance among different volcanic rock types. The present study revealed the level of physical properties of volcanic rocks, which are ranked as follows: volcanic breccia > mafic lava > tuff > felsic intrusive rock. However, the degree of fracture development ranked differently from most developed to least developed as follows: felsic intrusive rock > mafic lava > volcanic breccia > tuff. The fracture distribution was primarily controlled by lithology, rock stratum thickness, degree of weathering and leaching, along with tectonism. Compared to other rock types, felsic intrusive rock and mafic lava were more prone to fracturing owing to different petrophysical properties. Additionally, fractures typically developed in single lithological bodies with a thickness of less than 15 m and were characterized by the “single-section” developing mode. For lithological bodies of thickness greater than 15 m, fracture development was more limited, primarily concentrated at the top and bottom of the lithological body and characterized by the “bi-section” or “tri-section” developing modes. These differences can be quantitatively characterized by the fracture development thickness, fracture layer density, and fracture development thickness ratio. Moreover, the influence of the degree of fracture development on the productivity of mafic lava and felsic intrusive gas reservoirs was higher than that of the porosity; however, volcanic breccia and tuff exhibited the opposite effect. The production capacity of weathered volcanic crust reservoirs is affected by the following factors in the order of degree of fracture development > porosity > lithology > thickness of a single lithological body > distance from the top surface of the weathered crust. These quantitative characterization methods can provide valuable technical support for optimizing favorable exploration targets.

The Use of Formic Acid and Organic Mud Acid for Stimulation of Volcanic Rocks in Minami-Nagaoka Gas Field, Japan

Summary Unlike acid stimulation in sandstone and carbonate formations, acid stimulation of volcanic formations is not well documented in the literature, and its effectiveness and applicability are not well understood. This study aims to evaluate acidizing of volcanic rocks (especially rhyolite) as a well stimulation technique through a comprehensive experimental and modeling investigation using formation samples from a volcanic reservoir, the Minami-Nagaoka gas field in Japan. The experimental study consists of rock characterization, solubility tests, coreflooding tests, and batch reactor tests. The rock samples are investigated with computed tomography (CT) for textural characteristics and with X-ray diffraction (XRD) analysis for lithological characteristics. With these results, candidate acid systems are selected, and their effectiveness in terms of the capability of dissolving volcanic rocks is evaluated through acid solubility tests. Acid coreflooding tests are performed using undamaged plug cores to evaluate permeability responses caused by acid/rock reactions under high-temperature and high-pressure conditions (300°F and 3,000 psi, respectively). Batch reactor tests are conducted to quantify damage due to secondary/tertiary reactions. The mineralogical and textural characteristics of the rock samples let us select formic acid as the preflush acid and a mixture of formic acid and hydrofluoric acid (HF) called organic mud acid (OMA) as the main treatment acid. The composition of OMA was a mixture of 9% formic acid and 1% HF or 10% formic acid and 0.5% HF in this work. Results of the coreflooding tests with the preflush acid indicated permeability enhancement in all the samples and, especially in cores with cemented fractures filled by carbonate minerals, substantial permeability enhancement was observed. On the other hand, cores treated with OMA after the preflush indicated further permeability enhancement in some cases without cemented fractures, whereas other cases showed permeability impairment after the OMA injection. Furthermore, results of the batch reactor tests with formic acid indicated low precipitation risks, whereas those with OMA suggested higher precipitation risks. Detailed analysis on the thin sections and residuals of the batch reactor tests with OMA highlighted the precipitation of unique fluorides, and the precipitation risk was modeled and quantitatively evaluated with geochemical simulations. Although there is more room to investigate the risks of the usage of OMA for the volcanic rocks, the results in this work suggest the use of formic acid as a main treatment acid, as in carbonate acidizing, for wells with abundant cemented fractures in near-wellbore regions. This paper provides insights on acid stimulation in volcanic rocks (especially rhyolite). The results provide a fundamental understanding on the acid/rock reactions and the potential benefits/risks for productivity enhancement of wells in the subject volcanic reservoir.

Fracturing Optimization Design of Fractured Volcanic Rock in Songliao Basin Based on Numerical Research and Orthogonal Test

Abstract The efficient development of fractured volcanic reservoir relies on fracturing, while the existence of natural fractures has an important impact on hydraulic fracturing in this reservoir. There are few reports on fracturing optimization of deep volcanic gas reservoirs in Songliao Basin in China; thus, the parameter optimization under single-stage action is studied. On the basis of logging interpretation, coring observation, and seismic interpretation, the fracture development degree is obtained. By employing numerical simulation and orthogonal tests, hydraulic fracturing optimization design is carried out. The results indicate that the pumping rate of 0.01 m3/s/m and perforation direction parallel to the maximum principal stress are the optimum parameters for the studied volcanic reservoirs. In addition, multibranch seam expansion will occur when the displacement reaches 0.01 m3/s/m according to fracture morphology results after fracturing. And the research method has certain significance for improving the fracturing design of fractured reservoir in the research block.

The Main Controlling Factors and Logging Identification of Carboniferous Volcanic Reservoir in Chepaizi Area

The Main Controlling Factors and Logging Identification of Carboniferous Volcanic Reservoir in Chepaizi Area

Effect of hydration on Pore Structure and Physical Properties of Permian Basalt and tuff in Sichuan Basin during pressurized imbibition

The volcanic rock with developed pores is important reservoir for oil and gas, but its complex pore-fracture structural characteristics lead to the hydration reaction when the volcanic strata is invaded by drilling fluid or fracturing fluid, which brings great challenges to the drilling operation and oil and gas production in volcanic rock reservoir. In order to understand the influence of clay hydration on the pore characteristics and permeability of different types of volcanic reservoirs. In this paper, we selected distilled water as the imbibition solution, and obtained the variation law of pore structure and physical properties of Permian tuff and basalt in Sichuan Basin during pressurized imbibition through a series of indoor test methods. The results show that the clay content of tuff is high, and the clay hydration produces new cracks during soaking, which leads to the increase of nuclear magnetic porosity of tuff after soaking. At the same time, it also makes some unconnected pores connected with each other, resulting in the increase of rock permeability in the later stage of soaking. During soaking, mineral particles peel off, and some clay minerals are transported to pores and fractures under hydrodynamic action, resulting in the reduction of effective porosity of tuff. The basalt is dense with poor physical properties. There are almost no cracks in the rock soaked for 0–24 h. After soaking for 48 h, new cracks are generated in the rock, which may be caused by the increase of pore pressure in the rock. The mineral particles around the crack obviously fall off and block the pore throat, resulting in the reduction of rock permeability after soaking. This study provides not only helps for avoiding the occurrence of lost circulation, well collapse and other accidents, efficient and safe drilling, but also a theoretical basis for the development of hydraulic fracturing in volcanic reservoirs.

Petrophysical rock typing based on deep learning network and hierarchical clustering for volcanic reservoirs

With the rebound of international oil prices, complex non-clastic volcanic rock reservoirs have been gaining much attention from the scientific community in recent years. However, due to the complexity of volcanic diagenesis and the intensity of tectonic activity at its development location, volcanic reservoirs generally exhibit strong heterogeneity. In particular, the volcanic rock reservoir in Block Jinlong 2 is a low-medium porosity, ultra-low to low permeability reservoir with complex lithology and diverse storage spaces. Therefore, the author proposes a petrophysical rock typing method based on the VGG16 deep learning network and hierarchical clustering, which takes MCP curve images and physical data as input. First, the author uses the learning ability of the convolutional layer and max-pooling layer in the VGG16 network to extract the characteristics of each MICP curve. Second, through the PCA dimensionality reduction method, the feature of each picture is transformed into a low-dimensional feature vector. Then, the distance of the image feature vector and the distance of the physical point are combined into a new distance matrix, which is used as the input of hierarchical clustering. Finally, the scores of the Davies Boulding Index and Sillhouette Coefficient are used to determine the final clustering result. Comparing with the FZI and FZI* methods, this method has a better application effect in Jinlong-2 Block volcanic reservoirs. The volcanic rocks of Jinlong 2 are divided into 4 types. Type 1 has the best reservoir characteristics, type 4 is relatively compact, and type 2 and 3 are in the transition zone, but type 2 will develop some micro-fractures to increase reservoir seepage capacity. Such petrophysical rock typing has laid a good foundation for the subsequent reservoir description and reservoir evaluation research of Jinlong-2 Block volcanic reservoirs. • Volcanic rock reservoirs are highly heterogeneous, and petrophysical rock types are diverse. •VGG16 and Hierarchical Clustering for data-driven petrophysical rock typing. •Petrophysical rock types in the Jinlong-2 Block of Xinjiang Oilfield are divided into four types. •Results analysis by DBI and S score.

Lithofacies characteristics and controlling on volcanic reservoirs in the basement: A case study of the offshore Bohai Bay Basin, Eastern China

Volcanic rocks are important, but special reservoirs, for hydrocarbon exploration. Volcanic lithofacies play an important role in reservoir development, but the understanding of the relationship between lithofacies and reservoirs is still limited, especially for volcanic basements. In this paper, we characterized the intermediate-basic lithofacies features and discuss the relationship between lithofacies and reservoirs in the offshore Bohai Bay Basin. The results show that there developed volcanic conduit, eruptive (basic and neutral), explosive, and volcanogenic sedimentary facies in the study area. Among them, the explosive and eruptive facies are dominant. Different lithofacies present diverse well-logging and seismic responses, and the basic-eruptive (basalt), neutral-eruptive (andesite), explosive, and volcanogenic sedimentary facies are distributed from the bottom to top orderly fashion. This vertical superposition pattern represents a volcanic eruption process that has resulted in eruptive facies being more developed than explosive facies. The pores (intershard, dissolution, and devitrified pores) and tectonic fractures are the predominant spaces for explosive and neutral-eruptive facies (andesite), respectively. The lithofacies control the development of the primary spaces, fractures, and the diagenesis processes, leading to explosive and neutral-eruptive facies being the dominant facies for reservoir development. The understanding of high-quality reservoirs in the volcanic buried hills is not only controlled by weathering but also dominant lithofacies that will guide the volcanic exploration globally.

Evaluation of volcanic reservoir heterogeneity in eastern sag of Liaohe Basin based on electrical image logs

The volcanic rocks of the Es3 (third member of the Shahejie) formation in the eastern sag of the Liaohe Basin are composed of basalt and trachyte, and the reservoir characteristics indicate complex reservoir space and strong heterogeneity. The latter is closely related to oil and gas reserves, and is important for evaluating reservoirs and predicting their oil and gas production. Electrical imaging data are obtained during such analysis and are subsequently transformed into a porosity map to obtain the porosity spectra and bin distribution. The results can then be used to qualitatively study the heterogeneity of the reservoir. In the present study, however, quantitative analysis is applied to evaluate the reservoir diversity of these volcanic rocks by calculating four heterogeneity parameters: the sorting index and the porosity variation coefficient, porosity ratio, and the heterogeneity coefficient. Combining the porosity spectra and porosity bin features enables the reservoir heterogeneity to be divided into three categories. The first is weak heterogeneity, which has both a sorting index and variation coefficient of <0.15, a porosity ratio of <2, and a porosity heterogeneity coefficient of <1.5. The second is moderate heterogeneity, with both a sorting index and porosity variation coefficient of 0.15–0.25, a porosity ratio of 2–4, and a porosity heterogeneity coefficient of 1.5–2.0. The third is strong heterogeneity, with both a sorting index and porosity variation coefficient of >0.25, a porosity ratio of >4, and a porosity heterogeneity coefficient of >2.0. In these three cases, the porosity spectra are dominated by unimodal distributions, bimodal distributions with tails, or multimodal distributions with tails, respectively. The heterogeneity of the volcanic reservoir was controlled by the lithology. The trachyte, from which most oil and gas is presently produced, is characterized mainly by weak heterogeneity, and the basalt is characterized mostly by moderate or strong heterogeneity. Thus, exploration conducted in the basalt layer should consider reservoirs with moderate heterogeneity and large pore sizes.

The diagnostic criteria of borehole electrical imaging log for volcanic reservoir interpretation: An example from the Yingcheng Formation in the Xujiaweizi Depression, Songliao Basin, China

Electrical image log can be used to establish volcanic facies sequences, and thus used for reservoir interpretation, while the key is to set up available diagnostic criteria to guide lithology, structure and facies interpretation. A total of 50 datasets of borehole image logs, combined with wireline logs and cores, have been collected in the Yingcheng volcanic reservoir in the Xujiaweizi Depression, Songliao Basin, providing an opportunity for repeated image interpretation in the volcanic strata. The interpreted lithology includes rhyolite, dacite, andesite, basalt, welded ignimbrite, tuff, volcanic breccia and agglomerate, sedimentary tuff, sedimentary volcanic breccia and agglomerate. The volcanic structures are calibrated in terms of fluidal and deformed fluidal structure, vesicular and amygdaloidal structure, and massive structure. Based on the lithology and structures, volcanic facies including volcanic sedimentary facies, effusive facies, explosive facies and volcanic conduit facies, have been further determined. Layered structures of the weathered volcanic crusts are shown in borehole images and mainly developed at the top of the Yingcheng Formation. Borehole images indicate that SHmax direction in the area is consistent with the regional SHmax direction, with a preferable trending of 88°. Four sets of filled/open tectonic fractures are developed with approximately north, south, NNE and NW dipping. It infers that different volcanic facies can be well correlated between wells, and tectonic movements have a slight influence on the Yingcheng volcanic strata. The proposed diagnostic criteria and the workflow can be referred for a direct image interpretation in volcanic reservoirs or ocean drilling programs when cores are unavailable.

An Improved Scheme of Azimuthally Anisotropic Seismic Inversion for Fracture Prediction in Volcanic Gas Reservoirs

Seismic prediction of natural fractures is essential for the characterization of unconventional reservoirs because fractures provide seepage paths for fluid migration and storage space for hydrocarbon accumulation. However, it remains challenging to robustly estimate anisotropic parameters for fracture characterization based on seismic inversion methods. We propose an improved inversion scheme for the robust and accurate estimation of anisotropic parameters using PP-wave azimuthal amplitude differences incorporated with a hybrid optimization algorithm. Modeling analysis indicates that by removing the effect of isotropic terms, azimuthal amplitude differences are more sensitive to anisotropic parameters than the traditional azimuthal reflection coefficient; this can avoid possible instabilities in anisotropic parameter estimates that may occur in conventional methods owing to unbalanced weighting coefficients between isotropic and anisotropic terms. Meanwhile, the proposed hybrid algorithm takes advantage of the global optimization ability of the simulated annealing algorithm and the fast convergence characteristics of the particle swarm optimization algorithm. Synthetic data tests indicate that the hybrid algorithm achieves reliable and stable estimates of anisotropic parameters with higher computational accuracy and efficiency than traditional methods. The improved inversion method is applied to characterize fractures in volcanic gas reservoirs. Based on azimuthal amplitude differences obtained after estimating fracture orientation using the Fourier series method, anisotropic parameters are computed and converted to weakness properties, which is more meaningful in terms of the fracture properties. Our results indicate that the obtained fracture tangential weakness exhibits an apparent correspondence with well-log permeability, justifying the applicability of the proposed method for fracture prediction.

Characterization of Volcanic Reservoirs; Insights from the Badejo and Linguado Oil Field, Campos Basin, Brazil

Characterization of Volcanic Reservoirs; Insights from the Badejo and Linguado Oil Field, Campos Basin, Brazil

Processes controlling volcanic and epiclastic reservoir formation in a buried polygenetic stratocone

Abstract Understanding the formation of volcanic and epiclastic reservoirs is pivotal for exploring geoenergy resources such as geothermal energy, hydrocarbons, and new CO 2 sequestration and hydrogen storage opportunities. This paper examines the processes controlling the quality of pyroclastic and epiclastic reservoirs of the Kora volcano, an extinct stratocone presently buried in the offshore Taranaki Basin, New Zealand. We conduct detailed seismic reflection interpretation, drillcore lithofacies and wireline-log description, petrographic analysis, and analytical tests to generate a unified framework that explains the formation of volcaniclastic reservoirs from basin to pore-scale. Each stage of construction and degradation of the Kora volcano is associated with particular processes that increase or reduce reservoir quality. Primary processes include quench fragmentation, deuteric mineral dissolution, and epiclastic sedimentation. Secondary processes comprise mineral alteration (mainly meteoric; minor hydrothermal and diagenetic), mechanical stress fracturing (mainly tectonic; minor magmatic and burial deformation), and pervasive biogenic cementation. Epiclastic conglomerates present the highest reservoir quality (average 23% porosity and up to 997 mD permeability), followed by lapilli-tuffs and tuff-breccias. In contrast, bioclastic epiclastic sandstones are typically cemented by carbonates and pyrite. Our models and interpretations will increase understanding of the formation of volcaniclastic reservoirs and aid exploration of geoenergy resources in volcanic terrains.

Study on the effect of cemented natural fractures on hydraulic fracture propagation in volcanic reservoirs

Hydraulic fracturing has been widely used in tight reservoir to generate fractures to improve the conductivity and productivity. However, due to combined effects of volcanism, tectonic movement, and water dissolution in volcanic reservoir, characteristics and cementation strength of natural fractures are complex, and the propagation laws of hydraulic fracturing are complex. In order to study the influence of typical fracture characteristics of volcanic rocks on hydraulic fracturing and provide technical means for optimizing the favorable area of fracturing, numerical research was carried out. Considering the mechanical differences between natural fractures (NFs) and rock matrix, the cross verification is carried out based on indoor hydraulic fracturing tests and numerical simulation to confirm the reliability of the numerical method. In addition, the characteristics of typical NFs in volcanic reservoirs are obtained based on outcrop observation and core analysis, and hydraulic fracturing models are established by using stochastic modeling method. The results reveal that hydraulic fracture (HF)'s propagation rate will increase and initiation pressure will decrease with the decrease of cementation strength ratio. When the cementation strength of NFs decrease to 0.1, the propagation direction of HFs is also affected by the cementation strength and morphology of NFs significantly in addition to the maximum principal stress, and fracture networks will appear after fracturing. Therefore, the angle between the NF and the direction of the maximum principal stress is smaller, and the cementation strength is lower, the hydraulic fracturing effect is better under the same pumping pressure, which has important guidance for the selection of fracturing sweet spot and development of volcanic reservoirs.

Characterization of a Volcanic Gas Reservoir Using Seismic Dispersion and Fluid Mobility Attributes

Abstract Seismic dispersion and fluid mobility attributes are used to characterize a volcanic gas reservoir in the Songliao Basin of China. A rock physics model is constructed to describe poroelastic behaviors associated with heterogeneous fluids saturation within the volcanic gas reservoirs, where velocity dispersion and attenuation of propagating waves are attributed to the wave-induced fluid flow described by the patchy saturation theory. Modeling results indicate that the frequency-dependent bulk modulus at the seismic frequency is more sensitive to gas saturation than the P-wave velocity dispersion. Accordingly, a new inversion method is developed to compute bulk-modulus-related dispersion attribute DK for improved characterization of volcanic gas reservoirs. Synthetic tests indicate that DK is more sensitive than traditional P-wave dispersion attribute DP to the variations of reservoir properties. The high value of dispersion attribute DK indicates the volcanic gas reservoirs with high porosity and gas saturation. At the same time, fluid mobility attribute FM can discriminate the volcanic gas reservoir as DK. Field data applications illustrate that DK and FM exhibit anomalies to the gas zones in the volcanic gas reservoir on the cross-well section. However, DK is more robust than FM to identify favorable zones on horizontal slices for specific target layers. Overall, rock physical modeling provides insights into the poroelastic behaviors of volcanic gas reservoirs, and inversion for seismic dispersion attribute DK improves hydrocarbon detection in the volcanic gas reservoir.

Validity of geochemical signatures of abiotic hydrocarbon gases on Earth

Abiotic synthesis has been hypothesized as a mechanism for occurrences of hydrocarbon gases with atypical molecular and isotopic compositions. This paper provides biotic interpretations of these atypical compositions, as follows: (1) microbial CH 4 oxidation and CO 2 -sourced methanogenesis may enrich 13 C in hydrothermal CH 4 ; (2) microbial hydrocarbon generation using serpentinization-derived H 2 may deplete deuterium in hydrocarbons; (3) three processes may cause isotopic reversal with the carbon number in biotic hydrocarbons (the decrease of kinetic isotope effect (KIE) with the increase of carbon number during alkane biodegradation, inverse KIE during the thermal decomposition of higher alkanes and isotopic fractionation during gas diffusion in rock samples); (4) random scission of long alkyl chains may form the exponential distribution of alkane abundance with respect to carbon number (the ‘Schulz–Flory distribution’); (5) isotopic compositions are often not equilibrated; even if they are, the equilibrium temperatures are not necessarily the same as the temperature of hydrocarbon generation. Case studies demonstrate that previously proposed abiotic hydrocarbon gases in continental serpentinite-hosted seepages, continental or oceanic hydrothermal vents, volcanic emissions, gas fields in volcanic reservoirs and fluid inclusions in alkaline or granitic rocks were formed by various biotic processes. The occurrence of abiotic hydrocarbon gas with decisive evidence is limited to fluid inclusions in some mantle minerals. Supplementary material: Expressions for isotopic fractionation of CH 4 and model details of the Xujiaweizi gas are available at https://doi.org/10.6084/m9.figshare.c.5660278