煤层气固井声幅测井方法探讨

影响煤层气固井声幅测井的因素较多,如地层软硬变化大、套管内径或壁厚不均、仪器不居中、发射能量不足、接收灵敏度不够等,这些因素的存在将会导致首波丢失、时差曲线产生周波跳跃或波动现象。为提高煤层气固井声幅测井质量,要尽量保证所用仪器外径接近套管内径,以减少无效传播和能量损失,另外需提高仪器的发射能量及接收灵敏度;在自由套管和声波强吸收地层,必须保证自由套管首波不限幅、声波强吸收地层首波不丢失。在现场解释时,一般以＂自由套管＂处的偏转幅度值A为标准,将固井声幅曲线幅度的20%A和40%A作为分界点,评价固井效果。     

浅谈测井方法在工程勘察中的应用

地球物理测井应用于工程勘察中,能够较好地解决用钻探不易解决的问题,如有效判别薄夹层、寻找井旁隐伏断裂破碎带、判断孔内土层稳定性以及测定土层的速度等。其中自然伽马测井曲线在判定含砾粘土夹层及软弱薄粘土夹层等方面具有较高的准确性;声波、井径、自然γ、视电阻率等测井方法可有效查找井旁隐伏断裂破碎带,特别是声波测井曲线异常更为明显;另外跨孔实测剪切波速还可进行地基土加固效果检验。     

幔源CO_2释出机理、脱气模式及成藏机制研究进展

针对幔源CO2如何从地幔岩浆中脱出并进入沉积地层中形成CO2气藏聚集这一关键问题,总结了国内外研究进展和前缘方向。研究表明,地幔深部的碱性玄武岩浆和碱性岩浆才是深部流体和CO2等挥发份大量赋存、渗滤和释出的场所。浅成侵入岩、次火山岩和火山通道等是CO2释放和聚集的有利位置,岩浆期后和岩浆衰弱期的热液活动阶段是CO2大量释放和聚集的有利时期。幔源CO2进入沉积盆地中具有3种脱气模式,即沿岩石圈断裂直接脱气模式、热流底辟体脱气模式和壳内岩浆房-基底断裂组合脱气模式。CO2的固有物化性质决定其运移相态多样,具有运移和聚集过程同步的特征。只有在满足大量的化学消耗及地层水或原油的溶解和耗散之后才能形成CO2有效聚集。幔源CO2成藏和分布主要受岩浆气源体和气源断裂体系的控制。今后,在超临界CO2及其对油气运移聚集的作用、CO2与深大断裂及火山岩的关系、CO2脱气运移机制、CO与常规烃类油气的耦合差异成藏机制等方面仍需要进一步的研究和探索。     

苏里格气田盒8气藏气水层测井识别研究

鄂尔多斯盆地苏里格气田盒8气藏为弹性驱动的河流相低效气藏,储层非均质性强,在开发中普遍见水。根据试采情况将气藏储层分为气层、水层、气水层三类,开展气、水层的测井识别研究。以区内26口井50个射孔层段各层的试油结果作为依据,选出了700个样本点作为判识建模的标本,以声波时差和中子孔隙度等8个原始测井值作为判识变量组合,采用模糊判别分析,建立了各层的判识模型。回判结果表明,模型对气层精度达到97％,水层为89％,气水层为94％。利用未参加建模的出水井射孔段对模型进行验证,判识结果基本符合实际情况,模型具有较高精度。     

焦作-郑州天然气输气管道工程地质灾害防治措施及防治建议

焦作-郑州天然气输气管道是较重要建设项目,输气管道起自焦作市博爱县磨头镇,南止郑州市惠济区古荥镇,该输气管道沿线地质环境条件复杂程度为简单-中等。地质灾害类型主要为崩塌、地裂缝、地面不均匀沉陷,黄土湿陷和沙土液化等地质灾害。工程建设有引发和加剧崩塌灾害的可能性,有遭受地质灾害的危险性。工程建设过程中应针对不同的灾害类型采取适当的预防或治理措施。     

高位瓦斯抽放钻孔在降低综采工作面瓦斯浓度中的应用

林南仓属于低瓦斯矿井,但存在高瓦斯区域。煤层和采空区是瓦斯的主要来源,尤以采空涌出量大,给煤矿生产和安全带来了极大隐患。通过在1129综采工作面风道施工高位瓦斯孔,把钻孔打到采空区一侧煤层顶板以上冒落裂隙带内,用钻孔进行瓦斯抽放,使采空内的瓦斯通过裂隙带沿钻孔抽出,有效降低综采工作面瓦斯浓度,保证综采工作面正常回采和安全生产。     

数值模拟技术在海坨子油田开发调整研究中的应用

讨论分析数值模拟技术在海坨子油田开发调整研究中的思路和方法,采用美国Landmark公司VIP2003．4版本数值模拟软件包进行模拟研究,通过参数准备,静、动态拟合,模拟出海坨子油田海S9—11井组1—9砂组各小层剩余储量大小及不同阶段流体饱和度分布,结合可视化技术形象描述了海坨子油田剩余油变化规律及潜力区,在此基础上预测不同井网加密方式开发指标,并优选出最佳方案,为海坨子油田下步开发调整提供了重要依据,取得了较好的效果。     

Evolution of cool skin and direct air-sea gas transfer coefficient during daytime

Absorption of solar radiation within the thermal molecular sublayer of the ocean can modify the temperature difference across the cool skin as well as the air-sea gas transfer. Our model of renewal type is based on the assumption that the thermal and diffusive molecular sublayers below the ocean surface undergo cyclic growth and destruction, the heat and gas transfer between the successive burst events are performed by molecular diffusion. The model has been upgraded to include heating due to solar radiation. The renewal time is parameterized as a function of the surface Richardson number and the Keulegan number. A Rayleigh number criterion characterizes the convective instability of the cool skin under solar heating. Under low wind speed conditions, the solar heating can damp the convective instability, strongly increasing the renewal time and correspondingly decreasing the interfacial gas exchange. In the ocean, an additional convective instability caused by salinity flux due to evaporation becomes of importance in such cases. The new parameterization is compared with the cool skin data obtained in the western equatorial Pacific during the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment in February 1993. In combination with a model of the diurnal thermocline it describes main features of the field data both in nighttime and daytime. Under low wind speed conditions (< 5 m s^-1) diurnal variations of the sea surface temperature due to the formation of a diurnal thermocline were substantially larger than those across the cool skin. Under wind speeds > 5 m s^-1, diurnal variations of the surface temperature due to the variations of the thermal molecular sublayer become more important.     

Oil and gas resource assessment: The linkage between geological analysis and discovery process model results

Two widely-used techniques to estimate the volume of remaining oil and gas resources are discovery process modeling and geologic assessment. Both were used in a recent national assessment of oil and gas resources of the United States. Parallel estimates were obtained for 27 provinces. Geological-based estimates can typically see into areas not available to discovery process models (that is areas with little or no exploration history) and thus, on average, yield higher estimates. However, a linear relation does exist between the mean estimates obtained from these two methods. In addition, other variables were found in a multiple regression model that explained much of the difference. Thus, it is possible to perform discovery process modeling and adjust the estimates to yield results that might be expected from geological-based assessments.