Zhongfan, Wang (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Xiaodong, Wei (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Xin, Chen (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Hongmei, Wang (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Yaliang, Xia (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Suhong, Zhang (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Gang, Chen (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Yingxiao, Wang (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Yizhong, Wang (GRI, BGP, CNPC, Hebei Zhuozhou, 072750) | Dalu, Lin (Instrument Service Center of Equipment Department, BGP, CNPC, Hebei Zhuozhou, 072750)
Granite "buried hill" oil pool is an unconventional oil pool which can be formed a large and highly effective oilfield in some basins such as Bach Ho oilfield in Vietnam and Kharir oilfield in Yemen.However, the diversity of reservoir types and combination,highly heterogeneity, and monotony method of reservoir prediction restrict the reservoir prediction accuracy of the granite buried hill. With the development of acquisition and processing of wide azimuth seismic data, much more new methods can be used to improve the prediction accuracy in this paper.
Because of the complexity of the granite reservoir formation, it is too difficult to predict and evaluate reservoir only by one method. Through the past years study, workflows are developed mainly including three steps. The first step is classify the reservoir according to the reservoir space type based on the comprehensive analysis of core,outcrop,wireline, FMI data. The second step is summarize seismic response according to the different types of granite reservoir. The third step is use different seismic techniques to establish the corresponding predication workflow based on the seismic response and data situation.
Granite buried hill reservoir is divided into four types in vertical : weathering-leaching reservoir (A), fracture-vug reservoir (B), fractured reservoir (C) and tight granite (D). Different types of reservoir have obvious differences in core slice, wireline and FMI data. On seismic sections, reservoir A shows good continuity and high amplitude; reservoir B is different--some have good continuity and mid-high amplitude, and others have poor continuity and low-mid amplitude; reservoir C has poor continuity and low-mid amplitude.Reservoir A has the characteristics of low velocity and density, and is different in P-wave impedance from overlying clastic rock and underlying bedrock,thus it can be identified and predicted used by P-wave impedance inversion and amplitude spectrum gradient attribute.Reservoir B demonstrates the abnormal features of moniliform/punctate amplitude in amplitude spectrum gradient attribute which shows the development degree of solution fractures and vugs. Reservoir C can be predicted by post-stack attributes of volume curvature and coherence cube in a large scaleand then refined prediction used wide azimuth seismic data in a small scale, the fracture intensity and strike prediction results are matched the FMI data. The pre-stack fracture prediction can not only predict the fracture intensity, but also the strike. Totally, 11 of 13 well prediction results of fracture density and strike are matched well with drilled wells, and the coincidence rate is nearly 84%.
Using this technique series have obtained a good result in B Basin, which provide a technical reference for similar complex reservoir prediction and play more and more important role in granite reservoir prediction.
The ability to drill wells in high temperature formations is limited by the temperature specification of the available drilling tools. Most drilling tools currently have a temperature rating of 150°C, and there is an ongoing effort to develop tools with a higher temperature rating. A parallel effort is to develop the modeling capability to simulate the complex downhole temperature environment, to allow engineer to understand the temperature effect on drilling operation and better manage the temperature-related risks.
Many high temperature wells are planned in an extremely conservative manner. The engineer will rely on the formation temperature measured in offset wells to determine temperature gradient of the planned well. This temperature gradient will be used as a reference for all aspects of the well design, including drilling tools selection, cementing design, etc. In reality, there are many factors which affect the actual downhole temperature experienced by the tools. There is a complex interaction between heating from the formation, drilling fluid circulation, and the mechanical action of drilling tools. There are many forms of energy loss contributing to the downhole temperature, such as mechanical friction, rock cutting, and fluid friction.
A new state-of-the-art dynamic temperature model is developed to simulate downhole conditions in order to precisely predict downhole temperatures. This paper will explain the development of dynamic temperature modeling and how the model being used to plan high temperature well. The paper will also present several case studies where the modeling was used on planning high temperature well and comparison between model results and actual downhole temperature measurements.
Xing, Liang (PetroChina) | Chenggang, Xian (Schlumberger) | Honglin, Shu (PetroChina) | Xin, Chen (Schlumberger) | Jiehui, Zhang (PetroChina) | Heng, Wen (Schlumberger) | Gaocheng, Wang (PetroChina) | Lizhi, Wang (Schlumberger) | Haixiao, Guo (Schlumberger) | Chunduan, Zhao (Schlumberger) | Fang, Luo (Schlumberger) | Kaibin, Qiu (Schlumberger)
A shale gas field at the southern edge of the Sichuan basin, China, started its oilfield development plan (ODP) in early 2014. The first wells drilled in this field and its adjacent blocks experienced significant challenges, such as severe mud losses, stuck tools, losses in the hole, high treating pressure, and unexpected screenout. Because it is vital to have accurate understanding of geomechanics and its roles at various scales, three-dimensional (3D) full-field and pad geomechanics models were developed for achieving both efficiency and effectiveness during the ODP.
The work is based on high-resolution structural, geological, reservoir property, and multiscale natural fracture models. An extensive characterization of mechanical properties was conducted by the evaluation of cores, well logs, and seismic data. A systematic approach was implemented to build a 3D pore pressure model of the field. Finally, an advanced finite element simulator was used to compute 3D stress distribution, which fully owns all features and local changes of structural, geological, mechanical, and reservoir properties, and multiscale natural fracture models. The large model (80×80-m cell) covers the full field, and the pad model (20×20-m cell) covers a 15- to 20-km2 area. All have 0.5-m vertical resolution of the targeted sweet section to capture vertical heterogeneities measured from logs. Large-scale parallel computing technology was used to perform such massive geomechanical modeling. The models were calibrated or constrained by all available data such as mud logs, cores, borehole images, drilling data, prefracturing injection tests, hydraulic fracturing responses, microseismic events, and flowback data. All models were updated continuously when new data became available.
The computed stress models match the highly compressive background and current understanding of the dominant tectonic movements of the Sichuan basin. They are sufficient to reveal orientations, magnitudes, anisotropies, and heterogeneities of in-situ stresses. Large variations of in-situ stresses can be quantified among pads and wells and along laterals. Such variations correspond to or align with changes in texture and composition at various scales, such as faults and complex multiscale natural fractures. The full-field model was used to optimize pad and well locations and well trajectories and assess geological integrity, resources in place, and instability of natural fractures. The high-resolution pad models were used for near-wellbore stability analysis, real-time drilling management, engineering hydraulic fracturing design and monitoring, and integrated post-fracturing analysis. The implemented approach was proven to be effectively integrated into the progress of drilling and completion. This is the first time such 3D geomechanics models have been built for China's shale gas development. The knowledge and experience gathered can certainly benefit other similar projects.
Xin, Chen (BGP, CNPC.) | Xiaodong, Wei (BGP, CNPC.) | Hongmei, Wang (BGP, CNPC.) | Mingqiu, Zhao (BGP, CNPC.) | Wenyuan, Tian (BGP, CNPC.) | Yuwei, Wang (BGP, CNPC.) | Yanjing, Li (BGP, CNPC.) | Yaliang, Xia (BGP, CNPC.) | Xiaohuan, Yan (BGP, CNPC.) | Xiaomig, Zhou (BGP, CNPC.)
Pore pressure prediction before drilling is significant on ensuring drilling safety, reasonable drilling mud density, and designing well profile. It can also reduce the drilling cost and protect the hydrocarbon reservoir. With the increasing quality of seismic data and widely application of new methods, high-resolution seismic was used to reduce the uncertainty of the pore pressure prediction in this paper.
Through the past years study, workflows were developed which use the high resolution seismic for pore pressure prediction. The workflows mainly include three steps. The first step is the mechanisms analysis for pore pressure prediction. The geological genesis is the key to pore pressure prediction. Base on the geological genesis, Fillippone method was optimization and adjustment, such as seismic velocity analysis and variation rate of seismic velocity estimation based on geological consistency. After the method optimization, the overburden pressure and pore pressure will be estimated by the seismic data, integrated with regional geological data and shallow well logging data.
A postmortem from southwest of Iraq is presented showing a successful well that were better predicted before the well were drilled. The prediction result accuracy error is less than 5% compared with the measured data which is tested by well drilling and this indicates that the method can greatly improve the accuracy of pressure prediction before drilling.
With the increasing quality of seismic data, the high-resolution seismic data will play more and more important role in pore pressure prediction. The method integrated seismic, geological and well logging data for formation pressure prediction will reduce the uncertainty greatly.
Xin, Chen (GRI, BGP, CNPC) | Wei, Xiao-dong (GRI, BGP, CNPC) | Li, Yan-jing (GRI, BGP, CNPC) | Cui, Yi (Petro-China International Iraq, CNODC, CNPC) | Ma, Yingzhe (Petro-China International Iraq, CNODC, CNPC) | Yan, Xiao-huan (GRI, BGP, CNPC) | Xia, Yaliang (GRI, BGP, CNPC) | Wang, Guan (College of Geosciences, China University of Petroleum) | Wang, Xiaotian (College of Geosciences, China University of Petroleum)
Three-dimensional (3D) reservoir models are best created with a combination of well logs and 3D seismic data. However, the effective integration of those results in the reservoir modeling was not easy due to limited seismic resolution. With the increasing quality of seismic data and widely application of new methods, High-resolution seismic stochastic inversion volume was used as a direct input to reduce the uncertainty of the reservoir model in this paper.
Through the past years study, workflows were developed which use the high resolution seismic stochastic inversion as a direct input for reservoir modeling. The workflows mainly include three steps. The first step is target processing. Wavelet transform was applied to achieve noise elimination and resolution improvement. Base on the High-resolution seismic data, the second step is seismic stochastic inversion. After the process of time-depth conversion, the high resolution 3D data from seismic stochastic seismic inversion and well logs data were used to reservoir modeling as a direct input.
Experiment results show that noise elimination and resolution improvement achieved by using wavelet transform brings desirable convenience, high efficiency and good fidelity. The seismic response of sand reservoir in the high resolution seismic section becomes clearer than the seismic data before target processing, and matched with the well log interpretation. As the seismic stochastic inversion process is controlled not only by the acoustic impedance features, variographic model, and histogram, but also by high-resolution seismic data, the possible number of solutions is reduced, thus decreasing the nonuniqueness of the solution. The seismic stochastic inversion results were multiple 3D volumes with the same horizontal resolution of the seismic and with the vertical resolution, which is matched with the well data. The reservoir model base on the high-resolution 3D data from seismic stochastic inversion and well logs data will reduce the uncertainty greatly, especially in the area Where reservoir exhibits strong heterogeneity. A postmortem is presented showing a successful well that were better explained by this model result based on data existing before the well were drilled.
With the increasing quality of seismic data, and the progress of target processing, seismic stochastic inversion and reservoir modeling technology, the high-resolution seismic data will play more and more important role in reservoir modeling. High-resolution seismic stochastic inversion as a direct input for reservoir modeling will reduce the uncertainty of model greatly.
Four lithologies were developed in the study area and they were pore-bearing grainstone, compact sparite, shaly limestone and limy mudstone. The pore-bearing grainstone was the main reservoir rock. The characteristic analysis of the electrical and physical properties showed that the acoustic impedance of the pore-bearing grainstone was medium to relatively low. If we only use the inversion data of acoustic impedance, it is difficult to distinguish between the pore-bearing grainstone and other lithologies. In addition, it is difficult to distinguish the reservoir using any single given electrical parameter such as GR, density and resistivity. Therefore, we selected several sensitive logging parameters through crossplot analysis. On the basis of the geostatistical inversion, several volume data were combined, thereby the favorable reservoirs were determined.
The multi-parameter geostatistical inversion integrated and constrained by logging data and seismic data. It not only takes the advantage of the geostatistical inversion which does not simply use the acoustic impedance to joins the calculation, but it also uses the curves such as GR, porosity which directly reflect the lithology and physical properties of the formation, to join the calculation. Compared with the conventional acoustic inversion, it greatly improved the vertical resolution, finely characterized the distribution of the reservoirs, and better conquered the problem of the multiplicity of the reservoir prediction and resolution?
Manchao, He (School of Mechanics & Civil Engineering, China University of Mining & Technology) | Xin, Chen (School of Mechanics & Civil Engineering, China University of Mining & Technology) | Guoping, Liang (Beijing FEGEN software Co. Ltd) | Huashan, Qian (Beijing FEGEN software Co. Ltd) | Yongfa, Zhou (Beijing FEGEN software Co. Ltd) | Xiaoyan, Zhuang (Beijing FEGEN software Co. Ltd)
Weiyuan, Zhou (Department of Hydraulic Engineering, Tsinghua University) | Xin, Chen (Department of Hydraulic Engineering, Tsinghua University) | Chang, Steve (Schlumberger Corporation Beijing GeoScience Center) | Ruoqiong, Yang (Department of Hydraulic Engineering, Tsinghua University)