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26 April 2024, Volume 14 Issue 2
  • Question and comment for FETKOVICH’s typical curve
    CHEN Yuanqian,WANG Xin,LIU Yang,SHI Xiaomin
    2024, 14(2):  159-166.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.001
    Abstract ( 56 )   HTML( 66 )   PDF (1660KB) ( 66 )   Save

    FETKOVICH proposed the water influx rate equation in finite aquifer and the type curve with constant pressure in 1971 and 1980 respectively, which have been widely recognized and cited by experts both domestically and internationally. His methodology allows for the determination of a well's drainage radius and area by fitting actual production data to his type curve, a technique that has gained popularity among field experts. The derivation of this paper shows that the equation for water influx rate equation in finite aquifer of FETKOVICH is an is characterized by an exponential decline, a model he directly applied to analyze production declines in wells with volumetrically closed boundaries. He derived a dimensionless time for the type curve based on the relationship with the initial decline rate and used the inverse of dimensionless pressure as a proxy for dimensionless production to develop the type curve's dimensionless production profile. However, it's important to note that FETKOVICH's model does not establish a direct functional relationship between dimensionless time and dimensionless production in the type curve model, which means that a comprehensive dimensionless type curve cannot be formulated directly from his equations. This article deduces the water influx rate equation in finite aquifer and the dimensionless time and dimensionless production of the type curve, and questioned and commented on the existing problems.

    Theories, technologies and practices of exploration and development of volcanic gas reservoirs: A case study of Cretaceous volcanic rocks in Songnan fault depression
    MA Daixin,REN Xianjun,ZHAO Mifu,HAN Jiaoyan,LIU Yu...
    2024, 14(2):  167-175.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.002
    Abstract ( 49 )   HTML( 40 )   PDF (14668KB) ( 40 )   Save

    In the past two decades, Sinopec Northeast Oil & Gas Company has made significant strides in exploring the southern Songliao Basin, revealing that the basin's volcanic rocks present a new and promising avenue for hydrocarbon exploration. According to the exploration practice of the basin, the company has developed a comprehensive four-component coupling reservoir control model specific to fault depressions. This model emphasizes the interconnected evolution of key elements such as hydrocarbon generating foci, reservoir formation periods, paleostructure, fault cap preservation, and effective reservoirs, with a particular focus on the main accumulation period. This strategic approach led to the significant discovery of a large-scale volcanic gas reservoir within the Huoshiling Formation in the Changling fault depression, located in the Songnan area. Consequently, the exploration focus has broadened from the Yingcheng Formation to the Huoshiling Formation, diversifying the exploration targets from acidic volcanic rocks to intermediate-basic volcanic rocks, and extending from subaerial to submarine eruptions. By using the technique of fine gas reservoir description, the integration of modeling, numerical modeling and geological engineering, the productivity breakthrough has been achieved in several wells in Songnan fault depression, and the efficient development and large-scale production of volcanic gas reservoir has been realized.

    Characteristics and development model of underwater eruptive volcanic reservoirs in continental lacustrine basin: A case study of Chaganhua Subsag in Changling Fault Depression, Songliao Basin
    REN Xianjun,SHI Yunqian,JING Wei
    2024, 14(2):  176-189.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.003
    Abstract ( 35 )   HTML( 26 )   PDF (16987KB) ( 26 )   Save

    Industrial oil and gas have been found in the volcaniclastic rocks of the Huoshiling Formation erupted underwater in the continental lacustrine basin of the Changling fault depression in the Songliao Basin, which has broad exploration prospects. The study focuses on the reservoir space characteristics, physical properties and pore structure differences of the underwater eruption pyroclastic rock reservoirs in the Huoshiling Formation, and analyzes the reasons for the differences in physical properties of different types of reservoirs and their formation and evolution processes. There are mainly the following four aspects: ① Tuff, with its high volcanic glass content, predominantly features devitrification and dissolution pores as its main reservoir spaces. Coarser particle sizes in tuff correlate with improved physical properties, including larger and more abundant pores. Sedimentary tuff, rich in clay minerals, exhibits mainly interstitial spaces between these minerals and poorer physical properties. Tuffaceous sandstone, with high levels of soluble components like feldspar, debris, and laumontite, is characterized by dissolution pores. ② The average porosity is 2.43%, and the average permeability is 0.076×10-3 μm2. Coarse-grained tuff exhibits the highest porosity, followed by tuffaceous sandstone and fine-grained tuff, with sedimentary tuff displaying the poorest physical properties. ③ Devitrification significantly contributes to the high porosity yet ultra-low permeability observed in tuff reservoirs. Organic acid dissolution during the middle diagenesis stage, resulting from two separate oil and gas fillings, further enhances porosity. Additionally, fractures serve as conduits for organic acids and deep hydrothermal fluids, promoting further dissolution that connects dispersed dissolution pores and enhances reservoir space effectiveness. ④The coarse-grained tuff reservoir in the near-source facies gas-carrying subaqueous pyroclastic flow subfacies is a favorable target for oil and gas exploration.

    Research and application of productivity equation correction method for tight volcanic gas reservoirs
    QIU Yixin
    2024, 14(2):  190-196.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.004
    Abstract ( 31 )   HTML( 30 )   PDF (1652KB) ( 30 )   Save

    The binomial productivity equation is a pivotal tool for analyzing data in gas reservoir development, typically resolved using well test data. However, in tight volcanic gas reservoirs, the pressure remains stable and changes slowly, which can lead to challenges during productivity well tests. Specifically, the indication curve generated from measured data may have an intercept less than 0, rendering the equation unsolvable in its standard form, thereby necessitating a correction to the formula. Taking the Well-C2 of tight volcanic gas reservoir as an example, the reason of abnormal indication curve is analyzed. By reviewing and adapting existing equation correction methods, the bottom hole flowing pressure data from the productivity test well is adjusted, leading to the derivation of a new corrected binomial productivity equation. It is applied to the tight volcanic gas well, and the result is more stable than the result of single-point method. It can fully leverage the well test data and provide the basis for the calculation of open flow capacity and the formulation of subsequent development and production plan.

    Prediction of volcanic fractures based on prestack azimuthal anisotropy: A case study of LFS area in southern Songliao Basin
    LI Ning,MIAO He,CAO Kaifang
    2024, 14(2):  197-206.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.005
    Abstract ( 36 )   HTML( 27 )   PDF (8664KB) ( 27 )   Save

    Anisotropic parameter inversion based on pre-stack azimuth gather seismic data is one of the primary methods for fracture prediction, among which two algorithms, RüGER approximate equation and Fourier series expansion, are more widely used. Both the anisotropic gradient in the RüGER approximate equation and the second-order term in the Fourier series expansion can characterize the crack intensity. In the experiment, the applicability of applying this two equations was compared in the single-layer interface and the fracture layer of the actual drilled wells, respectively, and the fracture spatial prediction results were compared in the actual volcanic rock development zone. There are dimensional differences in the prediction of fracture strength between the two equations of single interface model. The range of fracture strength of RüGER approximation equation is larger than that of Fourier series expansion. Multiple results exist for the calculation of fracture orientation using the RüGER approximation equation, which may result in an orientation perpendicular to the fracture. However, when applied to the fractured layers observed in wells, both methods yielded broadly consistent results regarding fracture orientation and strength. In the application to the volcanic rock formation of the LFS area in the southern Songliao Basin, the Fourier series' second-order term slightly outperformed the RüGER equation in aligning with the fracture strength interpretations derived from electrical imaging logging. Additionally, the predicted fracture orientations from both methods matched those interpreted from imaging logging. It is concluded that the Fourier series equation for predicting fractures is more suitable for popularization and application in the field of volcanic rocks.

    Comparison, optimization and application of multiple prestack inversion algorithm for intermediate basic volcanic reservoirs: A case study of Huoshiling Formation in Chaganhua area
    LI Ruilei,CAO Lei,FAN Xuepei,FENG Xiaohui,LI Ning
    2024, 14(2):  207-215.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.006
    Abstract ( 33 )   HTML( 40 )   PDF (5625KB) ( 40 )   Save

    Currently, the most widely used pre-stack simultaneous inversion algorithm is based on the Zoeppritz equation approximation of isotropic horizontal media. This method, however, encounters challenges in medium-basic volcanic reservoirs characterized by rapid lateral lithological changes and vertical multi-period stacking. In such environments, tuffs and sedimentary tuffs exhibit similar logging and geophysical responses, complicating the distinction of lithology and physical properties of volcanic rocks through pre-stack simultaneous inversion. To address these challenges, qualitative analyses were conducted on the seismic response characteristics of volcanic reservoirs using convolutional model forward modeling. Additionally, well rock physics was employed for physical analyses of lithology and sensitive parameters pertinent to volcanic reservoirs. Comparative analyses of six binomial and trinomial pre-stack inverse algorithms, aimed at approximating the Zoeppritz equation in the specific area, were conducted through model calculations and actual data assessments. Based on these comprehensive analyses, the approximate algorithms developed by SMITH & GIDLOW and FATTI were identified as preferable choices. These algorithms use the reflection coefficients of P-wave impedance, S-wave impedance, and density as inputs for pre-stack inversion. The inversion results for P-wave impedance were utilized to predict the presence of local tuff, while the inversion outcomes for density were employed to ascertain the effective reservoir physical properties. The efficacy of this approach was validated through the deployment of an evaluation well and a horizontal well, which yielded predicted compliance rates of 76.0% and 84.6%, respectively.

    Establishing classification standards for volcanic reservoirs based on pore structure and nuclear magnetic logging: A case study of Chaganhua Gas Field in Songnan Fault Depression
    WANG Min,CAO Yue,LI Wancai,ZHAO Wenqi,WANG Wenyong...
    2024, 14(2):  216-223.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.007
    Abstract ( 34 )   HTML( 48 )   PDF (3877KB) ( 48 )   Save

    In the Chaganhua Gas Field within the Songnan Fault Depression, the Huoshiling Formation's volcanic reservoirs exhibit an average porosity of 4.5% and a permeability of 0.08×10-3 μm, indicating a dense and highly heterogeneous nature. Due to this complexity, a comprehensive approach, testing a broad set of reservoirs, is required to establish effective classification criteria. This study used physical property data, high-pressure mercury injection, nuclear magnetic resonance, and other experiments to analyze the microstructure of volcanic reservoirs. Through multi parameter comparison, a microscopic classification standard was established. Nuclear magnetic logging served as a bridge between microscopic and macroscopic parameters, facilitating the creation of a comprehensive evaluation framework for classifying volcanic reservoirs. This framework encompasses microscopic structural features such as pore throat radius, displacement pressure, mercury saturation, alongside macroscopic parameters obtained from nuclear magnetic logging and other experiments, such as the T2 spectrum distribution, centrifugal saturation, porosity, permeability, saturation, acoustic time difference, lithology density, and resistivity. Reservoirs are categorized from high to low quality into classes A, B, and C based on this comprehensive set of criteria. This method has strong operability and provides a reliable basis for the testing plan of new drilling and the optimization of sweet spots in exploration and development of horizontal wells. The research methods and understanding have certain reference significance for the classification research of volcanic reservoirs.

    Volcanic facies development characteristics of Yingcheng Formation in Songliao Basin: A case study of field outcrops in Jiutai area of Jilin Province
    SHEN Yanjie,LI Junru,ZHANG Liya,ZHOU Yang,CHENG Ri...
    2024, 14(2):  224-236.  doi:10.13809/j.cnki.cn32-1825/te.2024.02.008
    Abstract ( 25 )   HTML( 28 )   PDF (23023KB) ( 28 )   Save

    To explore the intricate relationship between volcanic rock types, volcanic facies, and genetic models within the Yingcheng Formation of the Songliao Basin, and to understand their implications for oil and gas exploration, a comprehensive analysis was conducted using a wide array of geological data. This included field outcrops, drilling data, and rock slices, allowing for the identification of volcanic rock types, classification of volcanic facies, and analysis of the genesis characteristics of these facies. It is concluded that: ①Four types of volcanic rocks are developed in Yingcheng Formation, which are lava, pyroclastic lava, pyroclastic rock, and clastic sedimentary rock; ②The outcrops of Yingcheng Formation are divided into five lithofacies types,which are crater facies-volcano channel type, crater-post volcanic type, near crater-volcano slope type, volcanic slope type and volcanic dome type; ③Two genetic modes of volcanic facies, crater accumulation genetic mode and volcanic slope genetic mode, are established.

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