Improving the resolution of seismic data processing is an effective means for predicting thin reservoirs. The primary objective of high-resolution processing is to effectively recover high- and low-frequency information of seismic data, broaden frequency bandwidth, and maintain signal-to-noise ratio and fidelity of seismic data. Using the high-resolution processing technology for restoring weak signals through harmonic decomposition, and based on compressed wavelet transform, the high- and low-frequency weak seismic signals were restored according to harmonic components. Firstly, the seismic signals within effective frequency bands were decomposed into various baseband signals by using the compressed wavelet transform. Then, the high-order and low-order harmonics of each baseband signal were calculated and added to the wavelet transform coefficients. Finally, inverse wavelet transform was performed to restore the high- and low-frequency weak signals. In this process, only the baseband signals within the effective frequency band are estimated, which helps to maintain the signal-to-noise ratio. The wavelet transform coefficients of seismic signals are consistent with the stratum reflection coefficients, verifying that the technology has high fidelity and good relative amplitude preservation. The actual application of the high-resolution processing technology shows that it can maintain the signal-to-noise ratio and significantly widen the seismic bandwidth, resulting in clearer seismic profile breakpoints, higher resolution, and better identification of thin reservoirs of about 40 m thick at the depth below 6 000 m.
Conventional pre-stack depth migration imaging techniques separate the migration imaging and static correction processing. In the processing of seismic data from complex mountainous areas, due to the factors such as complex surface condition, drastic lateral velocity variation near the surface, and exposure of high-velocity interval, the static correction based on the assumption of surface consistency may cause wave field distortion. This distortion leads to big errors in calculation of travel time, affecting the effects of depth migration imaging. To solve this problem, a full-depth modeling and imaging technique based on true surface migration was proposed. This technique starts with velocity modeling and travel time calculation from the surface elevation, and addresses static correction implicitly in the migration imaging process. It has been satisfactorily applied in the processing of complex mountainous data.
The seismic frequency enhancement processing method based on multi-layer residual network combines high-frequency well logging information with seismic data through an intelligent network. This method effectively improves vertical resolution while maintaining lateral continuity，facilitating the identification of thin reservoir beds. In the AMH area，the seismic data processed by conventional techniques enable only the identification of carbonates thicker than 30 m，but not of thinner beds. The seismic frequency enhancement processing method based on multi-layer residual network was proposed for application in this area. First，a training was performed using the multi-layer residual network，a deep learning network，with the near-wellbore seismic amplitudes as training data and the relative wave impedance data from well logging as training labels. Thus，a predictive model for relative wave impedance curve was obtained. By using seismic data as input，the deep network training model was solved to obtain a relative wave impedance data cube，and then a data cube of reflection coefficient corresponding to the frequency-enhanced seismic data cube was obtained. After analyzing the geological conditions of the target area，appropriate wide-frequency wavelet was extracted after calibration，and then convolved with the reflection coefficient cube，so that a frequency-enhanced seismic data cube was obtained. Reservoir inversion was performed using the frequency-enhanced seismic data cube. The inversion results are of high resolution vertically，well matching the main target beds，and can be identifiable and traceable laterally. Ultimately，the identification of thin beds in the AMH area was realized through the application of high-resolution seismic inversion results. The seismic frequency enhancement processing based on multi-layer residual network together with the corresponding high-resolution model inversion can identify beds thicker than 10 m in the AMH area. This method effectively addresses the problem of infeasible thin bed identification using low-resolution seismic data，and improves the accuracy in predicting thin beds. It is referential for identifying similar thin beds.
Fractured reservoirs are important exploration and development targets for increasing oil and gas reserves and production. The conventional post-stack seismic data can not meet the needs of fractured reservoir identification. This paper presents a method for the relative separation of reflected and scattered seismic wave fields based on diffusion filtering. This method predicts fractured reservoirs by adjusting diffusion coefficient and the number of iterations to separate the post-stack seismic data cube into 2 data cubes of reflection wave field and scattered wave field，and then extracting seismic attributes such as coherence，curvature，and ant tracking from the scattered wave field data cube. The method was applied to predict fractures in the weathered crust fractured bedrock reservoirs in the Songliao basin and the fractured reservoirs in the Maokou formation in the Sichuan basin. The results show that the method has higher resolution in predicting fractured reservoirs. The method was verified by the actual drilling data of two wells in the weathered-crust fractured reservoirs in the Daqing exploration area，showing a coincidence rate of 67%. This method can provide references for exploration，development，and well deployment in similar reservoirs.
The simulation methods and model precision adopted for layered modeling in 3D geological modeling vary with reservoir characteristics and research purposes at different development stages. From the perspective of 3D geological modeling，the reservoir development can be divided into three stages: reservoir evaluation，new block development，and existing block adjustment. The layered modeling algorithms were analyzed and selected for the 5th fault block in Gangdong district 2. It is proposed that the Kriging algorithm should be used for modeling at the reservoir evaluation stage，with a grid resolution of 100 m × 100 m × 5.0 m；the Kriging or Global B-spline algorithm should be used for modeling at the new block development stage，with a grid resolution of 50 m × 50 m × 1.5 m；and the Local B-spline or Converging average algorithm should be used for modeling at the existing block adjustment stage，with a grid resolution of 10 m × 10 m × 0.5 m. This modeling approach can provide results in more coincidence with actual geological conditions and can meet requirements for reservoir research at each stage.
The production stabilization and water-cut control of multilayer clastic reservoirs have always been a hot topic in oilfield development. At the medium-high water-cut development stage, oilfields usually exhibit obvious decline of production, scattered distribution of remaining oil, and prominent development conflicts between layers. For these oilfields, there is an urgent need for appropriate optimization and control methods to achieve sustained and stable production. Based on the Bayesian posterior probability method and reservoir streamline simulator, by applying a random maximum likelihood function, the history matching problem was solved and a space data set was constructed. Furthermore, by using finite-memory quasi-Newton gradient method, the data space set was inverted to predict the future. The transient flow velocity of the reservoir flow field was characterized by integrating Pollock streamline tracing method. Thus, a reservoir flow field reconstruction method based on data space inversion was proposed. This method allows real-time optimization of the reservoir injection-production parameters without the need for complex and repetitive calculations. It overcomes the limitations of traditional optimization methods in finely describing flow field evolution and fills the gap in the application of data space inversion in flow field optimization. Taking reservoir B in the Bohai oilfield as an example, the proposed method was used to reveal the mechanism of the reservoir injection-production structure optimization and intuitively demonstrate the process of reservoir flow field optimization. The field application results show that the overall water cut of the reservoir is relatively steady, the scattered remaining oil in the target flooding unit is effectively exploited, and the swept area of water flooding expands by 24.85%, indicating a remarkable flow field control effect. These digitalization efforts for reservoirs will provide valuable reference for the development and data-driven flow field control of similar medium-high water-cut oilfields.
The reservoirs controlled by deep and large faults are generally thick and deep. Therefore, a well cannot penetrate completely through an entire reservoir. For calculating the oil column height in fault-controlled reservoirs, a physical model of oil column height in fault-controlled reservoir was established. On this basis, the idea of the wellbore temperature profile extrapolation method was discussed, a formula for calculating oil column height with the conversion method of oil-water column pressure coefficient was derived, and the dynamic reserves inverse method considering the cuboid drainage area and the equivalent flow resistance method considering the influence of gravity were proposed. The four methods were applied to two wells drilled into a fault-controlled reservoir in Fuman oilfield of Tarim basin. The results show that the oil column heights calculated by the four methods are consistent, and the average oil column heights of the two wells are 675.39 m and 634.60 m, respectively.
The reservoirs in the Tahe Oilfield are complex and the remaining oil in the middle-lower part is difficult to recover. Based on the geological data and modeling results, a reservoir profile model considering reservoir type, fracture distribution and fracture-vug configuration was constructed. This model enables the displacement experiments for surface karst reservoirs, underground river reservoirs, and fault-karst reservoirs, and also the visual analysis of oil-gas-water multiphase flow. The remaining oil distribution before and after nitrogen-assisted gravity drainage (NAGD) was investigated, and the differences in enhanced oil recovery (EOR) for karst reservoirs of different genesis were compared. The results show that NAGD contributes to balanced displacement for karst reservoirs of different genesis, but achieves varying efficiency of EOR - by 12%, 9%, and 7% respectively for fault-karst reservoirs, surface karst reservoirs, and underground river reservoirs. The research findings help to understand the influence of reservoir types on NAGD, providing support to the advancement of EOR techniques for fractured-vuggy reservoirs.
To determine the collapse mechanism of karst caves in carbonate reservoirs, through stress field simulation, and based on orthogonal two-dimensional sections of the karst caves, a two-dimensional mechanical model was established to simulate the stress distribution characteristics of the carbonate karst caves under negative pressure. By multiple linear regression on controlling variables, a karst cave collapse model coupling with the stress function of the critical fracture point was constructed to predict the relationships among cave collapse and stress, depth and width. It is found that the most important factors influencing cave rock burst and collapse are overlying formation pressure, reservoir compressive strength and flexural strength. For two caves superimposed vertically, when their vertical distance is less than 0.3 times the cave radius, the partition between the two caves breaks, leading to the cave connection. During the collapse and rupture, the cave height changes obviously, while the width changes slightly.
The western Qiulitag structural belt is an important successive area for oil and gas exploration in the Kuqa depression, Tarim basin. Its complex surface and underground geological conditions bring challenges to seismic survey. It has been less explored in the main structural belt, where the high steep structural features and complex fault systems cannot be depicted by using previous 2D (single-line and wide-line) seismic data. To address this problem, a combination of wide-frequency band, wide-azimuth and high-density 3D seismic survey and high-density cable 3D seismic survey is used to increase the effective folds in the complex, high, steep structural areas. The microlog-constrained shallow surface velocity modeling is conducted to improve the static correction accuracy in complex mountainous areas and thick gravel-covered piedmont areas. The six-division method for denoising is adopted to improve the signal-to-noise ratio of seismic data in inter-salt and pre-salt structures. The five-dimensional interpolation and regularization technique is applied to mitigate the impact of irregular observation system in mountainous areas on pre-stack depth migration imaging. Moreover, two-way wave reverse time-migration is performed to increase the migration imaging precision of highly steep formations. Through acquisition-processing integration and seismic-geological fusion, the seismic imaging precision in the western Qiulitag structural belt can be significantly improved.
The continental shale reservoirs in the Lucaogou formation of the Jimsar sag in the Junggar basin are lithologically composed of dolomite, argillaceous dolomite, dolomitic mudstone, dolomitic siltstone, and siltstone. The mechanical properties and energy evolution of the continental shale were investigated through laboratory mechanical experiments. The results show that there are significant differences in the rock mechanical properties of different lithologies within the shale reservoir. The compressive strengths of dolomite, dolomitic siltstone, siltstone, argillaceous dolomite and dolomitic mudstone are 112.09 MPa, 98.20 MPa, 85.98 MPa, 81.28 MPa and 58.30 MPa, respectively. With the increase of confining pressure, the brittleness of the rock samples of the continental shale reservoirs decreases and the ductility increases. The rock samples with different lithologies have different energy levels at the peak strength, indicating strong heterogeneity. Furthermore, the total energy, elastic energy and dissipated energy of the rocks with same lithologies under triaxial compression are higher than those under uniaxial compression.
Faults and fractures are developed in the marine carbonate gas reservoirs on the right bank of the Amu Darya basin. Water is active locally, which leads to severe water invasion during development. Through high-temperature and high-pressure displacement experiments on full-diameter core samples from complex fractured reservoirs, the influences of fracture permeability, fracture penetration degree and water volume multiple on water invasion in gas reservoirs were analyzed. The water invasion patterns in different fractured core samples were investigated by considering the dynamic changes in the water-gas ratio (WGR). The results indicate that as the fracture penetration degree, fracture permeability, and water volume multiple increase, the slope of the WGR curve under the corresponding water invasion pattern increases, suggesting more severe water invasion and channeling. The areas with incomplete fracture penetration can effectively restrain any sudden water invasion. Accordingly, the characteristics of water invasion patterns were further analyzed by using the water invasion diagnosis curves, and the index chart for diagnosis of water invasion in the study area was optimized.
In China, the abundant low-medium maturity shale oil resources present a huge potential for in-situ conversion. To evaluate the stimulation capability of low-medium maturity shale oil reservoir during in-situ conversion, in-situ heating experiments were conducted on the typical low-medium maturity shales from Chang 7 member of Yanchang formation in Ordos basin and Lucaogou formation of Jimsar sag in Junggar basin. By using techniques such as nuclear magnetic resonance testing, vertical optical microscopy observation, computerized tomography scanning, and pulse decay gas permeability measurement, the dynamic changes in nano-scale pores, thermal fractures, porosity and permeability under high-temperature and high-pressure conditions during in-situ conversion were monitored in a real-time manner. The kerogen pyrolysis-induced fractures and the hydrocarbon generation pressurization effect are key factors for significantly improving the microstructure and reservoir properties. Once the temperature exceeds the threshold (400°C), the extension, density, complexity and connectivity of fractures within the shale significantly increase due to kerogen pyrolysis and thermal expansion of hydrocarbons. Secondary pores with diameters ranging from 2 to 50 nm become dominant in the pore structure. Under in-situ stress, the porosities of the two types of shale can be increased by 3.65 and 2.73 times, respectively, while the permeability can be increased by 624.09 and 418.37 times, respectively. Permeability is more stress-sensitive in the high-temperature stage than in the low-temperature stage. Shale reservoir with lower in-situ stress and higher kerogen content exhibit higher stimulation capability and higher thermal fracturing and thermal permeability enhancement capabilities during in-situ conversion.
Bottomhole flowing pressure (BHFP) is a key factor determining the rational production system of coalbed methane (CBM) wells for purpose of long-term stable production. The constant mass model (CMM) is not applicable to the wells with double-layer commingled production, since it does not consider the acceleration pressure drop (APD) in the reservoir interval and the mass variation in well sections. Additionally, the BHFP in the lower reservoir is taken as a control parameter for the two intervals, which does not meet the adjustment requirements of the upper reservoirs. In this paper, the APD expression was decomposed and derived, the relationship between APD and the radial flow rate per unit length was established, and the pressure drop formula for the reservoir interval with radial inflow was derived. The reservoir was divided into multiple intervals, and the pressure drop calculation method for each interval was established. Based on the gas/water flow rates in each well section, the corresponding equations for calculating gas/water phase velocities were derived. Combining the above equations, a variable mass model (VMM) was established. The production data were input into the VMM and CMM for comparative verification. The results show that when gas and water are co-produced, the error of the VMM is 2.75%-6.58%, while the error of the CMM is 7.15%-15.18%, indicating that the VMM is more accurate. The BHFP differs significantly in the two reservoir intervals, with the maximum difference of 47.3%. Therefore, it is necessary to adjust the production system depending upon the respective BHFP of the two reservoirs. The VMM can accurately provide BHFP for each commingled interval, so it agrees more with the field conditions. It also avoids the problem of using the same BHFP for both intervals, which hinders precise adjustment of the production system. Thus, the new model provides a technical support for developing optimal production strategies and achieving high and stable production.
To determine the fluid saturation under the formation conditions of thin oil reservoirs in the Turpan-Hami basin, based on the data of sealed coring in the Wenmi oilfield and Shanshan oilfield, physical simulation control experiments were performed to simulate the influences of depressurized degassing and evaporation losses on core fluid saturation during coring, and then a fluid saturation correction model suitable for sealed coring of thin oil reservoirs in the Turpan-Hami basin was established. The limit of depressurized degassing loss is clarified, that is, when the initial water saturation is greater than 88% or less than 33%, the depressurized degassing loss is weak and negligible. The new model also takes into account the effects of pore volume change, extraction loss in saturation experiments, and evaporation loss under different flooding conditions on saturation measurement, effectively improving the correction accuracy. The error between the oil saturation derived from the model and that from logging interpretation is 0.17%.
The mathematical models for production cycle of oil and gas reservoirs were reviewed systematically. On this basis, the generalized functional production decline formula was introduced to replace the decline function in the generalized whole-process mathematical model for production cycle, and it is no longer necessary to determine the decline function according to the driving type and flow characteristics of the oil and gas reservoirs. Meanwhile, considering that the generalized whole-process mathematical model for production cycle can be integrated, the expressions of its increasing function items were summarized to form three types of increasing function expressions. When the composite time and undetermined parameters take different values, the new generalized whole-process mathematical model for production cycle can not only be converted into the basic mathematical models for various production cycles, but also form other new mathematical models for production cycle, possessing the general formula and extensibility in the whole-process mathematical model for production cycle. In order to reduce the difficulty in solving the undetermined parameters, five simplest and most common methods for solving the composite time formula and functional mathematical model for production cycle are given. The satisfactory application results verify that the new model is worthy of promotion in other oil and gas reservoirs.
The oil and gas reservoirs in the Qiketai formation of Middle Jurassic in the Pubei area of Taibei sag, Turpan-Hami basin, are controlled by lithology. Early exploration confirmed that there are thin oil-bearing sand layers with the thickness of 6-15 m at the bottom of the Qiketai formation. It is difficult for conventional inversion methods to predict these sand layers and these methods often yield large errors due to the limitations of the frequency band of seismic data. In order to improve inversion accuracy, a facies-controlled geostatistical inversion method based on low-frequency model optimization was proposed. Combined with the characteristics of large structural relief and greatly varying sedimentary facies in the study area, the low-frequency model was established by combining the compaction trend correction method and the seismic attribute constraint method to obtain the deterministic inversion results. On this basis, a facies-controlled model was established for facies-controlled geostatistical inversion, thus enabling the identification of thin sand layers in the study area. This method effectively complements the low-frequency information missed in seismic signals, and improves the longitudinal resolution of the inversion results. By using this method, a thin sand layer with the thickness of 7 m can be identified, and the inversion result is basically consistent with the actual thickness of sand body, which confirms the effectiveness of this method in predicting thin sand layers in Pubei area.
The ultra-deep formations in the Kuqa depression are rich in oil and gas resources，with strong reservoir heterogeneity and obvious well-to-well productivity difference. The present-day in-situ stress plays an important role in wellbore trajectory design，horizontal well operations，and fracturing design，but the current research methods are disadvantageous in many aspects. On the basis of the measured present-day in-situ stress，the relationship between in-situ stress and logging parameters was constructed，and the prediction of the present-day in-situ stress in the ultra-deep tight sandstone reservoirs in the Bozi gas reservoir of Kuqa depression was realized by using BP neural network. The results show that BP neural network is an effective method for predicting in-situ stress，with just a small error between the predicted and measured in-situ stress values，which is generally less than 10%. In the Lower Cretaceous of the Bozi gas reservoir，the maximum horizontal principal stress is the largest，followed by the vertical principal stress，and the minimum horizontal principal stress is the smallest. Generally，the strike-slip stress mechanism is universal，and the maximum horizontal principal stress is predominantly NE-SW trending in the east and NW-SE trending in the west of the Bozi gas reservoir. Compared with sandstone intervals，the sandstone-mudstone interbedding interval exhibits a stronger fluctuation of in-situ stress and a sudden high in-situ stress locally. The horizontal wells drilled along NE-SW direction in the east of the Bozi gas reservoir and along NW-SE direction in the west are relatively stable，while the vertical wells are prone to collapse.
In the upper Es4 in Y184 well block，northern Bonan subsag of Zhanhua sag， multi-stage fan delta deposits are developed，and characterized by thin sand bodies individually，great variation laterally and sandstone interbedded with shale，making it very difficult to perform quantitative prediction，which restricts the efficient development of this well block. Through deep learning and seismic attribute prediction，virtual wells were constructed to solve the problem of insufficient training samples for deep learning in the study area. Thus，a nonlinear relationship between sand body thickness and seismic attributes was clarified，and a network model for predicting sand body thickness using seismic attributes was established. This method can accurately predict sand body thickness and lateral distribution with a significantly improved accuracy，and provides a new idea for the prediction of tight sandstone reservoirs.
In order to realize the identification of the connected fractured-vuggy structures in the Tahe oilfield，based on the seismic interpretation results of large-scale reservoirs，together with the drilling，logging，testing，tracer and other data，the reservoir types in near-well and inter-well areas were identified. By identifying the reservoirs with static and dynamic monitoring methods，the characteristic parameters of the dynamic methods for identifying reservoirs in fractured-vuggy units were determined to improve the reliability of the identification. Depending upon the types of reservoirs identified with static and dynamic methods，the connected fractured-vuggy structures were constructed according to their in spatial position relationship. The application in the identification of single-well fractured-vuggy structures in the X unit reveals that the proposed comprehensive method is more reliable in identification of fractured-vuggy structure than a single static or dynamic method.
