Wide azimuth seismic data play an important role in deep reservoir prediction. According to the Paleogene clastic rock reservoir prediction, the high-density and wide azimuth 3D seismic data acquisition of ocean bottom nodes was first carried out in a Chinese offshore oilfield in 2019. After high precision amplitude-preserving processing, we obtained the high-quality wide azimuth gathers. However, the research on anisotropy and reservoir prediction using wide azimuth seismic data mainly focuses on carbonate and bedrock intervals, which is not suitable for clastic rock reservoir prediction. Therefore, this paper innovatively proposes a clastic rock reservoir prediction method, which studies prestack reservoir prediction in the ray parameter domain based on wide azimuth ocean bottom node seismic data. Based on the azimuth gathers, we can obtain elastic parameters through prestack amplitude versus offset inversion, which is used to characterize the reservoir, so it is significant to obtain high precision elastic parameters in order to get highly reliable reservoir prediction results. In this paper, we develop an amplitude versus offset inversion method based on the Bayesian theory in ray parameter domain, the output of which is density, P-wave impedance and Vp/Vs. These elastic parameters have high precision, and density data are valuable input for reservoir characterization because they are sensitive to the lithology of clastic rock reservoir at different orientations. In ray parameter domain inversion, the ray path of seismic wave propagation is considered polyline, which is more consistent with the actual situation; thus, extracted amplitudes of P gathers used in inversion are more accurate. In addition, the reflection coefficient formula in ray parameter domain has higher precision when the incident angle is large. The inversion based on the Bayesian theory can improve the stability of the inversion. Test on the actual data shows that the result of ray parameter domain inversion with a Bayesian scheme is more accurate, stable and reliable. Based on the above high precision density inversion results, an innovative wide azimuth data reservoir prediction technology based on elliptical short-axis fitting was proposed. The actual prediction of the deep reservoir in the Bohai oilfield shows that sand thickness fitting prediction results in the short axis can best match the actual drilling sandstone thickness. The coincidence rate is 86% and the short-axis fitting results are more in agreement with geological laws. Theoretical research and practical applications have shown that this method is feasible and effective, with high prediction accuracy, computational efficiency and strong application value.

The A oilfield in the Bohai bay is a near-source glutenite fan delta lithologic structural reservoir that has been discovered in the steep slope zone at the edge of the bulge area. The reservoir of A oilfiled has large sedimentary thickness (140 m thick), complex sedimentary lithology, and large differences in physical properties. Moreover, due to the high cost of offshore drilling and low well control, exploration and development urgently need to predict the reservoir deposition pattern, reservoir structure and distribution characteristics. In order to solve this problem, firstly, we established quantitative sedimentary microfacies geological parameters based on field geological investigation, and combined multi-professional data to determine the geological sedimentary model and sedimentary law. Secondly, the target processing to improve the resolution of seismic data is carried out, and the ability to distinguish sedimentary fan body stages is improved. And then, based on glutenite petrophysical analysis and variable-parameter seismic forward modeling, we have a more accurate understanding of the seismic response characteristics of the sedimentary fan. Finally, based on the prestack inversion technology of complex lithofacies sensitive parameters, the dominant reservoir distribution area of glutenite was quantitatively predicted. Through systematic research, we have a clear understanding of the glutenite sedimentary model and the distribution area of dominant reservoirs. Using the prestack inversion technology based on complex lithofacies sensitive parameters, the predominant reservoir prediction for the near-source glutenite fan delta sedimentary lobes was completed. The research results guide the evaluation of glutenite reservoirs, the design and implementation of development plans. The development well 13 implemented on this basis have a success rate of close to 100

The rock coring of the reservoir in the Bohai A field is difficult. The cores of the target section in the study area are loose, making it difficult to accurately measure the core-bound water saturation. The purpose of this research was to develop and validate a method for calculating a reservoir core-bound water saturation ratio using the cast thin section. First, pepper noise denoising and image enhancement were performed on the thin section by median filtering and gamma variation. Based on this, the enhanced sheet images were thresholded for segmentation by the two-dimensional OTSU algorithm, which automatically picked up the thin section pore-specific parameters. Then, the thin section image was equivalent to a capillary cross-section, while the thin film water fused to the pore surface was observed as bound water. For hydrophilic rocks with a strong homogeneity, the area of thin film water in the pore space of the sheet was divided by the total area of the pore space, which produced the bound water saturation. Next, the theoretical relationship between the film water thickness and the critical pore throat radius was derived based on the Young–Laplace equation. The bound water saturation of the rock was calculated by combining the pore perimeter and the area that was automatically picked up from the thin film for a given critical pore throat radius of the rock. Finally, 22 images of thin sections of sparse sandstone from the coring well section of the study area were image processed using the new method proposed in this paper, and the bound water saturation was calculated. The calculated results were compared with 22 NMR-bound water saturations and 11 semi-permeable baffle plate-bound water saturations in the same layer section. The results showed that the bound water saturation values calculated by the three methods produced consistent trends with absolute errors within 5%. The calculated results confirm the reliability of the method proposed in this paper. This method can effectively avoid the problem of the inaccurate results of core experiments due to the easy damage of sparse sandstone and provides a new idea for the accurate determination of the bound water saturation of sparse sandstone.

The landing process of horizontal wells requires high accuracy of depth prediction. In the region with severe lateral velocity variation, the accuracy of the traditional method of predicting depth by using the time-depth relationship of exploration wells cannot meet the demand at all. On the other hand, at present, horizontal wells cannot perform sonic logging during landing and cannot produce synthetic seismograms, which result that a refined time- depth relationship can’t be obtained and the process of depth prediction will be influenced. The acoustic curve prediction technology based on support vector machine can predict the acoustic curve according to the existing shale content curve and resistance curve. This method can produce synthetic seismic records and obtain a fine time- depth relationship. The accuracy of this method is greatly improved compared to traditional methods. Finally, this method is applied to the landing of horizontal well W5H of Bohai A Oilfield and the error of predicted depth and actual drilling depth is 2m, which ensured successful landing of horizontal wells. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2022 in Houston, Texas.

The conventional reflection coefficient inversion assumes that the seismic wavelet is time-invariant, but due to the influence of factors such as stratum absorption and attenuation, the actual seismic wavelet will change when it propagates in the underground medium. If the time-varying nature of the wavelet is not considered in the inversion, it will lead to inaccuracy in the inversion result. Considering the time-varying nature of seismic wavelets, this paper introduces a time-varying factor in the reflection coefficient inversion, and realizes the L1 norm constrained reflection coefficient inversion based on the time-varying wavelet. As a result, inversion results with higher accuracy than conventional methods can be obtained. This method was applied to improve the quality of seismic data of thin interbedded reservoirs in Bohai P oilfield, and highresolution seismic data was obtained, which achieved good application effects in subsequent reservoir research work. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2021 in Denver, Colorado.

Oil field A, situated in Bohai Bay, was discovered in 1999 and has been developed as one of the most productive oil assets in China. It continues to hold significant growth potential for the future. Though the field contains a large amount of resources remaining to be developed, seismic imaging has been challenging in area 5, resulting in structural uncertainty for reservoir interpretation and well planning. In the past three decades, several 2D and 3D seismic surveys have been acquired, processed, and reprocessed in this area. However, due to the existence of complicated gas clouds, which are shallow, multilayered, and extensive, obscured sub-gas-cloud images appear in all legacy seismic results, making fault interpretation under the gas clouds almost impossible. To improve the sub-gas-cloud image and overall structural interpretability, a narrow-azimuth full-field ocean-bottom cable (OBC) acquisition was conducted in field A during 2018 and 2019, and later, a compressive seismic imaging (CSI)-based full-azimuth and large-offset OBC infill survey was acquired in area 5, covering the widest gas cloud. Through high-fidelity signal processing, full-waveform inversion (FWI)-driven velocity model building, and imaging using both Kirchhoff migration and reverse time migration (RTM), the seismic image quality beneath complicated gas clouds is improved significantly. It is the first time that sub-gas-cloud faults and the Base of Guantao event have been imaged by seismic without significant dim zones. CSI acquisition, FWI, and RTM are the key elements to resolve gas-cloud-related challenges in area 5.

In response to the rapid implementation of development wells drilling and quick search for replaceable potential, it is needed to qualitatively evaluate the potential of the sandbody rapidly. In recent years, with the advantages of fast and efficient, post-stack seismic hydrocarbon detection technology has been applied widely at oilfield production stage. However, it is not effective on water layer with strong seismic amplitude on seismic profile or seismic attributes on the plane. Therefore, with the PLT (Production Logging Tool) data and logging curve analysis, we introduce the amplitude-variations-with frequency (AVF) inversion on the basis of the theory of seismic frequency absorption and attenuation for hydrocarbon detection. This method can utilize a variety of sources of information, such as logging data and seismic attributes, so the predicted results are more reliable. The prediction result of oil or water layer has a consistent rate of 90% with the actual data of the 27 newly drilling wells. What is more, through logging curve cube calculation along horizon, it can make a prediction for the distribution of oil and water, and the oil-water contact recognition result is very close to the proven oil-bearing area map by drilling wells. Presentation Date: Wednesday, September 27, 2017 Start Time: 11:25 AM Location: Exhibit Hall C/D Presentation Type: POSTER

Fluid discrimination is quite important for offshore oil exploration which always means high risks and investments. The goal of the study is to predict the fluid content of the reservoirs in the B oilfield of Bohai Sea. As a normal heavy oil field, precise fluid discrimination is a challenging task. In order to overcome the challenge, a modified Poisson impedance (PI) attribute named Fluid impedance (FI) and a consequent multi-attribute inversion method are adopted. The Fluid impedance (FI), which is based on Poisson impedance, is more sensitive to the fluid content since it is calculated through the correlation analysis between PI curves of different rotation angles and water saturation logs. Then the multi-attribute inversion method based on Probabilistic Neural Network (PNN) is applied to get the water saturation volume for fluid discrimination. What’s more, the use of Fluid impedance, along with other hydrocarbon related seismic attributes has resulted in a much improved prediction of water saturation volume with high resolution and accuracy. The application demonstrates that the proposed method can improve the reliability of fluid discrimination significantly. Presentation Date: Wednesday, October 19, 2016 Start Time: 8:50:00 AM Location: 156 Presentation Type: ORAL

The shallow oil and gas fields of the Bohai Sea are dominated by fluvial deposition, large lateral variations of the reservoir, and a complex oil-water relationship. Horizontal wells must be deployed within the high quality reservoirs with good physical properties and high permeability so as to improve the productivity of the oil wells. Therefore, the reliability of reservoir prediction becomes extremely important. In this paper, on the basis of analyzing the petrophysical characteristics and seismic response characteristics of the reservoir, we proposed the phase-controlled reservoir prediction technology, which combines reservoir prediction and reservoir cause; studied the distribution law of the high quality reservoirs of the NB Oilfield by using phase-controlled reservoir prediction technology; deployed and drilled the development wells on this basis, and obtained good results. Key words : Fluvial facies; Reservoir prediction; Phase-controlled; Main parameters of seismic waves

Oilfield C is located in the west of Bohai Bay, China. It is an advantageous position for accumulation of hydrocarbon because it is a local block between the Nanpu depression and Shaleitian uplift. The main reservoir in this area is a buried hill draping bioclastic dolostone of Paleogene age, sandwiched between the basement lithology of Palaeozoic carbonate and a large set of Neocene claystones. These stratum form the effective combination of reservoir and cap rock. There are four exploration wells in Oilfield C, among which two wells (C1 and C3) drilled the bioclastic dolostone with an average thickness of 20 meters (Figure 1). The low success rate of 50 percent confirms the bioclastic dolostone characteristic of limited extent and thickness, and high variation and heterogeneity, from which reservoir prediction of this bioclastic dolostone is very difficult. Geologic Setting From the exploration experience of the study area, the major control factor of the bioclastic dolostone is paleogeomorphology, in which the platform margin is the most favorable sedimentary position due to its high energy wave action, shallow water and sufficient sunshine, yet the upper and lower position is not suitable for reservoir development (Figure 2). The paleogeomorphic restoration can effectively predict the range of bioclastic dolostone and has been applied successfully to the peripheral oilfields, however, there is the premise that the structure of the marker horizon used for horizon flattening is true which cannot be met in Oilfield C. The drilled wells revealed that a set of volcanic rock developed in shallow strata, characterized by complex lithology, high velocity and uneven distribution (Figure 3), because of which several lateral velocity variations occur in the volcanic-covered area. The structure of strata is distorted by the lateral uneven distribution of these volcanics, so the result of reservoir prediction obtained from paleogeomorphic restoration cannot truly represent the distribution of bioclastic dolostone. As a result, drilling of the bioclastic dolostone reservoir has resulted in two dry holes due to the reservoir prediction error of the bioclastic dolostone. Identification of volcanics To solve the problem of time-depth conversion in the area covered with volcanics, an integrated workflow has been innovatively established to identify volcanics and improve the reservoir prediction accuracy. 1) First, the preliminary map-view distribution of the volcanics is obtained from the average amplitude attribute: high amplitude area is related to effusive basalt; low amplitude area is related to explosive tuff; the translation area with medium amplitude is related to mixed rock composed of basalt and tuff in varying proportions (Figure 4). 2) Second, the top and bottom interfaces of volcanics is interpreted based on the mechanism of volcanic eruption and the above results of map-view distribution (Figure 5). 3) Third, the lithology of volcanics are characterized by both high-speed basalt and low-speed tuff, however, only the portion of highspeed basalt causes the lateral variation of velocity, so we get the thickness of high-speed basalt by innovatively establishing the relation between the interval velocity of volcanics and the proportion of high-speed basalt. 4) Last, considering the fact that the thickness of basalt also affects the velocity, we introduce the binary regression to restore the true structure, by establishing the relation between velocity and T0 (representative of compaction), thickness of basalt (Figure 6). By identifying the volcanics, we get the true structure and restore the paleogeomorphology of the bioclastic dolostone, based on which we predict the distribution range of bioclastic dolostone (red rim in the Figure 7). Conclusions The reservoir prediction calculated from the integrated workflow matches the new drilling results very well. Recently an appraisal well (orange star in the Figure 7) was drilled, which revealed 25 meters of bioclastic dolostone. This integrated workflow and its result not only improved the prediction accuracy of the reservoir distribution, but also provides valuable references for paleogeomorphic restoration in areas of false structure image. Figure 1. Cross section of four exploration wells. Figure 2. Sedimentary face of isolated carbonate platform. crosssection distribution Of faces fan delta (nearshore subaqueous fan)---open basin system carbonate platform ---open basin system highest lake level

It is the key of using the oil layer efficiently to avoid the top gas reservoir of the oil and gas reservoir in the development of the offshore oilfield. The oil reservoir in the second member of the Shahejie Formation of the Jinzhou South Oilfield in the Bohai Sea is a complex oil and gas reservoir of top gas, narrow oil ring and edge water. The oil and gas reservoir is longitudinally divided into multiple sets of fluid systems, and the gas-oil interfaces of different fault blocks are not consistent with large differences. The positions of the gas-oil interfaces and oil-water interfaces need to be determined precisely in the development and design of the horizontal wells on the drilling platforms, so as to prevent the premature gas channeling and water invasion of the production wells. Thus the identification of the top gas reservoir is particularly important. In this paper, we used seismic attribute analysis, pre-stack elastic parameter coordinate rotation method fluid detection and other technologies to identify the top gas reservoir of the oil and gas reservoir in the second member of the Shahejie Formation of the Jinzhou South Oilfield in the Bohai Sea, and obtained good application effects. Key words : Oil and gas reservoir; Top gas reservoir; Three-dimensional seismic high resolution amplitude preservation processing; Seismic attributes; Pre-stack elastic parameter coordinate rotation method; Fluid detection

In Bozhong M Oilfield, the target reservoir is deep buried, and the frequency of the seismic data is low; the conventional inversion technology is less effective. For these facts, taking into account the thin interbedded sandstone-shale reservoir, make full use of the advantages of the trace integral technique respecting the original seismic data, we further study the reservoir distribution. Based on the polarity analysis of the seismic data and verification of synthetic seismogram, it gets a trace integral data volume which agrees well with the drilled wells and can reflect the property and thickness of the main reservoirs. It optimizes the attributes of sum of positive amplitude, accurately forecasts the distribution of the main reservoir and the reservoir thickness of the infill wells. In the shallow, by optimizing the attributes of minimum amplitude, a good channel sand body is discovered, and the proven oil geological reserve is 290×104 m3. In this new discovered sand body, 4 wells doubled the oil production, and realized stereo efficient development of M oilfield.