新场气田沙溪庙组多层致密气藏开发调整方案研究
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摘要
致密砂岩气藏在我国的天然气生产中占有相当大的比例，这类气藏具有低丰度、低孔隙、低渗透、低单井日产的特点，如何高效地开发多层叠置的大型致密砂岩气藏在国内外尚处于探索阶段，对于立体开发调整方案的研究更是少见报道。位于四川盆地西部川西坳陷中段的新场气田，是由浅、中、深层多个气藏纵向上叠置而成的大型致密碎屑岩气田，其产量位于全国前列。沙溪庙组JS_2气藏是该气田的绝对主力气藏，纵向上由四个气层组成；2000年编制开发方案，2002年达到设计生产规模，至今已超规模生产近6年。目前，气藏的稳产形势十分严峻，及时对气藏的开发做出合理的调整是气藏开发面临的首要任务。
本次研究是在利用各种地质资料、实验资料、地球物理资料和开发动态资料的基础上，采取静态预测与动态分析相结合、地质研究与开发动态相补充的思路，利用三维地质建模和气藏数值模拟技术手段对新场气田沙溪庙组JS_2气藏进行了以储层精细地质模型研究为基础，以储层和储量的定量评价为目标，以剩余气分布研究为核心的多学科定量一体化研究，最终形成以提高采收率和经济效益为目的的调整方案，为气藏下一步的开发提供直接、有效的指导。
在气田开发过程中，从现场获得的第一手资料逐渐增多，对气田的认识日趋全面，多层压裂技术愈发成熟，原订方案对气藏开发的指导作用已显不足。基于此，本论文主要从以下几个方面对新场气田沙溪庙组JS_2气藏进行再认识，并提出相应的整体调整方案：
(1)气藏基本特征描述：通过200余口井测井资料的小层精细对比并借助于地震解释成果，对JS_2气藏的构造特征、沉积微相、砂体展布进行了精细描述，结果表明，JS_2气藏为一平缓鼻状构造，三角洲平原水下分流河道为其主要沉积微相，4套砂体厚度较大、分布稳定。通过对储层岩性、物性(孔隙度和渗透率)、成岩作用、非均质性等的描述，认为储层物性差，微观非均质性较强，绿泥石和方解石的大量存在和不均匀分布是其主要原因。通过对区内产水井的综合分析后认为，地层水不活跃，主要分布在气藏边部，没有统一的气水界面。储层在地震、测井上的响应特征明显，测井曲线上“低自然伽玛、低中子、低密度、高声波、中等电阻率”特征能很好的识别不同类别的储层，地震上“低频、强振幅、低阻抗”的含气响应模式能准确的对储层进行平面预测；通过对JS_2气藏特征的描述，综合构造形态、储层性质、流体分布后认为，沙溪庙组JS_2气藏是受构造和岩性双重控制的孔隙型异常高压弹性气驱致密气藏。
(2)气藏三维地质建模：在JS_2气藏综合描述的基础上，根据地质统计学理论，应用地质建模软件Petrel，在变差函数控制下模拟了岩相的100个实现并从中优选出与地质认识最相符的作为最终岩相模型。在此基础上，应用相控随机建模方法，在岩相模型的控制下分别模拟了孔隙度、渗透率、含水饱和度、声波、电阻率五个参数的各100个实现，并各自优选出与实际匹配程度最高的实现作为最终模型。根据建立的定量参数模型，结合不同气层的特征，确定了储层分类标准并对其进行了分类评价。研究区内JS_2~2、JS_2~4以Ⅰ、Ⅱ类储层为主；JS_2~3以Ⅲ类储层为主，Ⅰ、Ⅱ类储层仅局部分布；JS_2~1虽以Ⅰ、Ⅱ类储层为主，但比其它气层要差。
(3)储量复算与评价：本次研究采用容积法和随机建模法两种方法对储量进行计算。容积法是在原有探明储量的基础上，根据气藏新增的大量动、静态资料，利用新建的解释模型对储量计算中的各个参数进行了重新计算和确定，最终得出沙溪庙组JS_2的气藏储量为463.75×10~8m~3，其中JS_2~1、JS_2~2、JS_2~3、JS_2~4的复算储量分别为104.85×10~8m~3、167.75×10~8m~3、46.56×10~8m~3、144.60×10~8m~3。复算后比原有探明储量(534.35×10~8m~3)减少了71.6×10~8m~3，减少的层位主要为JS_2~3、JS_2~4，减少的原因主要是含气面积的缩小。随机建模法计算储量是在三维随机建模的基础上，把整个储层分为若干网格，视每一个网格上的储量参数为随机变量，对于每一组随机变量，利用容积法进行储量运算后再进行网格积分，从而得到储量的一系列实现值。然后根据储量的分布作密度函数曲线和累计概率曲线，便可获得不同可信度的储量值。该方法既紧密结合了气藏的地质模型，又得到了不同可靠程度的储量数据，使储量结果更为客观。随机建模法计算所得的概率储量P_(90)为470.71×10~8m~3，与复算储量相差不大，误差为1.5％。在储量复算的基础上，依据储层分类和电阻率高低并结合测试产能对储量进行了分类与评价，Ⅰ类储量186.37×10~8m~3，占总复算储量的40％，无阻流量在5×10~4m~3以上；Ⅱ类储量183.33×10~8m~3，占总复算储量的39％，无阻流量在2×10~4m~3以上；Ⅲ类储量97.23×10~8m~3，占总复算储量的21％，属低效储量。除JS_2~1气层外，其他三层的Ⅰ、Ⅱ类储量共288.45×10~8m~3，均已动用。
(4)气藏综合调整方案研究：通过对沙溪庙组JS_2气藏开发方案的实施情况及开发效果来看，无论是地质认识还是开发层系及开发井网的确定、单井配产及生产规模的设计基本上符合气藏的实际情况，但因生产规模一直高于方案设计而造成稳产期缩短。气藏目前面临的主要问题是，一方面稳产困难，另一方面采出程度低，未动用储量数量大。剩余储量研究结果表明，气藏目前的剩余储量大，由两部分组成，一部分为低效储量，因没有生产井控制而未能动用，各气层均有分布，但主要分布在JS_2~1，JS_2~3气层；另一部分为相对优质储量，虽然已经动用，但因与生产井井距较大，依然保持了较高的地层压力。因而，气藏的稳产可以从两方面着手，其一是利用多层(双层或三层)压裂技术，纵向上动用低效储量，使之与相对优质储量合采；其二是部署调整井(含挖潜井)以提高可动用储量的采出程度，新增动用储量和新增可采储量将为气藏的继续稳产提供储量基础。针对不同类别探明储量及剩余储量的分布状况，部署调整井66口，设计调整方案3套，方案1不增加新井并对现有老井降产40×10~8m~3，使之平均日产量在240×10~4 m~3左右；方案2在方案1的基础上补充31口新井；方案3在方案2的基础上再补充35口新井。利用Eclipse数模软件在历史拟合的基础上，对各套方案的开发指标进行了动态预测，结果表明，增加新井后，气藏的累计采气量和采出程度明显增加和提高，方案3比方案2更优。通过66口调整井的实施，采气量增加32.7×10~8m~3(其中8.91×10~8m~3来自于JS_2~1、JS_2~3)，采出程度提高6.5％，气藏的稳产期延长5年，推荐方案3作为JS_2气藏的调整方案。
本文研究中的创新点为：
1、首次采用随机建模法对JS_2多层致密气藏的储量进行了计算。该方法不但体现了容积法储量计算中的地质概念，又充分考虑了储量计算参数的不确定性，融积分法与统计模拟法于一体；计算结果用概率的方式表达，在一定程度上规避了常规方法只获得一个储量值而不能对这一储量的准确性进行评估的缺陷。
2、首次针对多层致密气藏提出了经济与次经济储量并举、通过多层压裂技术和调整井的实施达到经济储量带动次经济储量的立体开发及调整思路。根据这一思路编制了JS_2气藏的立体开发调整方案，这对过去只注重于经济储量动用的大中型多层叠置气田的高效开发具有重要的指导和借鉴意义。
3、将现代油气藏管理的两大技术手段—储层建模和数值模拟融为一体，用于多层致密气藏立体开发调整方案研究之中。形成了一套以储层精细地质模型为基础，以储层和储量的定量评价为目标，以剩余气分布研究为核心的致密气藏开发调整方案研究技术体系。
Tight sandstone gas reservoir is of low richness, low porosity, low permeabilityand low individual well producing rate, however, it produced natural gas in a largeproportion in our country. At present, how to exploit efficiently the large multi-layerssuperimposed tight sandstone gas reservoir is still in the preliminary stage in theworld, and don't even mention the research on the three-dimensional adjusteddevelopment plan. The Xin Chang gas field, which located at the middle section ofthe western Sichuan depression in the west part of Sichuan basin, is a large tightclastic gas field imposed by many gas reservoirs vertically. Its production lies in thetop list in our country. JS_2 reservoir, the main producing reservoir and consisting fourgas formations, produced in 2000, achieved the designed production in 2002 and ithad been producing over the designed for almost six years. Now it is difficulty toproduce steadily, so, now, the proper & timely adjustment for the gas reservoir is ourfirst target.
Based on the various geologic formation, experimental, geophysical and dynamicdata, adopted by the methods of static prediction with dynamic analysis, used by themeasures of three-dimension geological modeling and numerical simulation, JS_2 gasreservoir has been quantitatively key researched on the unproduced gas distributionwith the goal of quantitative evaluation, which aims to improve the recovery andeconomic efficiency and to provide the direct & efficient guide for the furtherdevelopment.
During the process of development, more and more data & knowledge achievedand more advanced fracturing technology results in the even less steering function tothe reservoir development for the original plan. That is why this article focuses on theissues as following:
(1) Basic features description of gas reservoir
The fine description of structural characteristics, sedimentary microfacies andsand body spread based on the 200 wells log and the seismic data, indicates that JS_2 isa flat nose structure, the main sedimentary microfacies are distributary river course ofdelta plain with four thick & stable sand bodies. A large amount of chlorite and calcite presented and their uneven distribution lead to worse physical properties and strongmicro non-homogeneous property by the description of reservoir lithology, physicalproperty, diagenesis and non-homogeneous property. The comprehensive analysis onthe water produced wells shows that formation water exits in the formation edge andwithout unified boundary between gas and water. There are obvious characteristicsreflected on the log curve and seismic data, such as low natural gamma ray, lowneutron, low density, high sonic and medium resistivity, which can distinguish thereserves, low frequency, strong amplitude and low resistance, whose gas -bearingresponse module can give the plane prediction to the reserve. From the above researchwork, it is concluded that JS_2 is a kind of porous tight gas reservoir with abnormalhigh pressure, driven by gas and controlled by structure and lithology.
(2) Three-dimension modeling of gas reservoir
Based on the comprehensive description above mentioned, according to thegeological statistics theory, adopted by modeling software Petrel and under the controlof function, we simulated 100 actualizations and selected the final module whichhas the best conformity with geological knowledge. Besides, used by the method ofrandom modeling and under the control of petrofacies module, we simulated 100realizations individually for five parameters including porosity, permeability watersaturation, sonic and resistivity, and also selected the final actualization as the finalmodules which have the best conformity with facts. In accordance with the obtainedparameter module, combined with the characteristics of various gas formation, weset down the classification criteria of reserve and at the same time, we made anevaluation as listed: on the range of research area,ⅠandⅡreserves dominate in JS_2~2and JS_2~4 reservoirs, JS_2~3 withⅢreserve andⅠandⅡreserves local distributed andJS_2~1 withⅠandⅡreserves of worse quality.
(3) Reserves recalculation and evaluation
Reserves recalculated by using the volumetric method and the stochasticmodeling method in this paper. Based on the original proved reserves and accordingto the abundant dynamic and static datum, each parameter in the volumetric method isrecalculated and confirmed by using the new interpretation model. It is obtained thatthe reserves of Sha Xi Miao reservoir (JS_2) is 463.75×10~8m~3 through the volumetricmethod, and the reserves of each layer (JS_2~1, JS_2~2, JS_2~3, JS_2~4) is respectively104.85×10~8m~3, 167.75×10~8m~3, 46.56×10~8m~3, 144.60×10~8m~3. The recalculatedreserves has decreased by 71.60×10~8m~3 compared with the original proved reserves which is 534.35×10~8m~3. The layers of decreased reserves are JS_2~3, JS_2~4, the reason isthe decreasing of area. The stochastic modeling method is based on thethree-dimensional stochastic modeling, through dividing the whole reserves layer intoa lot of grids, considering the reserves parameters in each grid as stochastic variables, and performing grid integral for each group of stochastic variables after reservescalculation by the volumetric method, and a series of realized values of reserves arefinally figured out. Then reserves datum of different reliability can be obtained bydrawing the density function curves and accumulative probability curves according tothe distributing of reserves. This method is not only combined with geologic modelclosely, but also reserves datum of different reliability is obtained, which makingresults more external. The probability reserves P_(90) is 470.71×10~8m~3 through thestochastic modeling method. The value is close to that of recalculated reserves and theerror is 1.5%. Based on the reserves recalculation, reserves is classified and evaluatedaccording to layer-sorting, resistivity-sizing, and testing productivity. Reserves ofgradeⅠis 186.37×10~8m~3, which is 40% of the total, and AOF is more than 5×10~4m~3.Reserves of gradeⅡis 183.33×10~8m~3, which is 39% of the total, and AOF is morethan 2×10~4m~3. Reserves of gradeⅢis 97.23×10~8m~3, which is 21% of the total andbelongs to low- profit reserves. Except JS_2~1, reserves of gradeⅠandⅡof other layershave been produced which is totally 288.45×10~8m~3.
(4) Synthetic adjustment plan research of gas reservoir
According to the execution schedule and development effect of the developmentplan of Sha Xi Miao JS_2 reservoir, not only geologic cognition but also developmentlayer series, well pattern, product of single well, and production scale are accord withthe practice of reservoir. But the production scale is always higher than the designedscale, which results in that the stable production period has been shortened. The mainproblems the reservoir faced are that it is difficult to keep production stable, on theother hand, recovery percent of reserves is rather low and un-produced reserves israther great. Remained reserves research shows that the present remained reserves ofreservoir is great which is composed of two parts. One is low- profit reservesdistributing in every layer but mainly in JS_2~1, JS_2~3, which can not be produced due tohave no well controlling. The other is relatively high grade reserves which keepsrather high formation pressure due to big well spacing although has been produced.Thus there are two ways to keep production stable. One is to use commingledproducing wells between low- profit and high grade reserves through multi-layer fracturing technology, the other is to dispose adjustment wells (including wellwork-over) to increase recovery percent of producible reserves. Newly-increasedproduced reserves and producible reserves will provide keeping production stablewith substantial bases. According to the distribution of different grade of reserves andremained reserves, 66 adjustment wells are disposed and three adjustment programsare designed. The first program decrease present wells production by 45×10~4m~3without adding new wells and makes daily production to the level of 240×10~4m~3. Thesecond program adds 31 new wells on the base of the first program. The thirdprogram adds 35 new wells again on the base of the second one. The dynamicdevelopment indexes of each programs have been forecasted by using ECLIPSEsoftware based on history matching. The results show that the cumulative productionand recovery percent is obviously increased and the third program is better than thesecond one. Through disposing 66 adjustment wells, the production is increased by32.7×10~8m~3 (8.91×10~8m~3 from JS_2~1 and JS_2~3), the recovery percent is increased by6.5%, and the stable production period is extended by 5years. Thus the third programis recommended to be the adjustment paln of the reservoir.
This paper has three innovative points:
1. The reserves of multi-layer tight reservoir JS_2 is calculated by using stochasticmodeling method for the first time. This method combines integral method withstatistical simulation, which not only exhibits geologic conceptions in the volumetricmethod, but also considers the uncertainty of calculative parameters of reserves. Theresults is expressed by the way of probability, and to some degree, evades thelimitation that traditional methods can only obtain one reserves value but evaluate theveracity of the value.
2. Economic reserves and hypo-economic reserves are both considered aimed atmulti-layer tight gas reservoir. The method of three-dimensional Adjustment Plan forhypo-economic reserves being driven by economic reserves by multi-layer fracturingand implementing of adjustment wells. According to this idea, the three-dimensionalAdjustment Plan has been drawn. It has important direction and reference significanceto high-efficient development of large and middle scale gas fields, only the economicreserves of which are produced in the past.
3. The two technologies of modern reservoir management-reservoir layermodeling and numerical model combine to one part, which is used to researchthree-dimensional Adjustment Plan of multi-layer reservoir. A researching technology system for tight reservoir Adjustment Plan has been formed, which is based on thefine geologic model, making a target of quantitative evaluation for reservoir layersand reserves, and taking the distribution of remaining gas as the researching point.
本次研究是在利用各种地质资料、实验资料、地球物理资料和开发动态资料的基础上，采取静态预测与动态分析相结合、地质研究与开发动态相补充的思路，利用三维地质建模和气藏数值模拟技术手段对新场气田沙溪庙组JS_2气藏进行了以储层精细地质模型研究为基础，以储层和储量的定量评价为目标，以剩余气分布研究为核心的多学科定量一体化研究，最终形成以提高采收率和经济效益为目的的调整方案，为气藏下一步的开发提供直接、有效的指导。
在气田开发过程中，从现场获得的第一手资料逐渐增多，对气田的认识日趋全面，多层压裂技术愈发成熟，原订方案对气藏开发的指导作用已显不足。基于此，本论文主要从以下几个方面对新场气田沙溪庙组JS_2气藏进行再认识，并提出相应的整体调整方案：
(1)气藏基本特征描述：通过200余口井测井资料的小层精细对比并借助于地震解释成果，对JS_2气藏的构造特征、沉积微相、砂体展布进行了精细描述，结果表明，JS_2气藏为一平缓鼻状构造，三角洲平原水下分流河道为其主要沉积微相，4套砂体厚度较大、分布稳定。通过对储层岩性、物性(孔隙度和渗透率)、成岩作用、非均质性等的描述，认为储层物性差，微观非均质性较强，绿泥石和方解石的大量存在和不均匀分布是其主要原因。通过对区内产水井的综合分析后认为，地层水不活跃，主要分布在气藏边部，没有统一的气水界面。储层在地震、测井上的响应特征明显，测井曲线上“低自然伽玛、低中子、低密度、高声波、中等电阻率”特征能很好的识别不同类别的储层，地震上“低频、强振幅、低阻抗”的含气响应模式能准确的对储层进行平面预测；通过对JS_2气藏特征的描述，综合构造形态、储层性质、流体分布后认为，沙溪庙组JS_2气藏是受构造和岩性双重控制的孔隙型异常高压弹性气驱致密气藏。
(2)气藏三维地质建模：在JS_2气藏综合描述的基础上，根据地质统计学理论，应用地质建模软件Petrel，在变差函数控制下模拟了岩相的100个实现并从中优选出与地质认识最相符的作为最终岩相模型。在此基础上，应用相控随机建模方法，在岩相模型的控制下分别模拟了孔隙度、渗透率、含水饱和度、声波、电阻率五个参数的各100个实现，并各自优选出与实际匹配程度最高的实现作为最终模型。根据建立的定量参数模型，结合不同气层的特征，确定了储层分类标准并对其进行了分类评价。研究区内JS_2~2、JS_2~4以Ⅰ、Ⅱ类储层为主；JS_2~3以Ⅲ类储层为主，Ⅰ、Ⅱ类储层仅局部分布；JS_2~1虽以Ⅰ、Ⅱ类储层为主，但比其它气层要差。
(3)储量复算与评价：本次研究采用容积法和随机建模法两种方法对储量进行计算。容积法是在原有探明储量的基础上，根据气藏新增的大量动、静态资料，利用新建的解释模型对储量计算中的各个参数进行了重新计算和确定，最终得出沙溪庙组JS_2的气藏储量为463.75×10~8m~3，其中JS_2~1、JS_2~2、JS_2~3、JS_2~4的复算储量分别为104.85×10~8m~3、167.75×10~8m~3、46.56×10~8m~3、144.60×10~8m~3。复算后比原有探明储量(534.35×10~8m~3)减少了71.6×10~8m~3，减少的层位主要为JS_2~3、JS_2~4，减少的原因主要是含气面积的缩小。随机建模法计算储量是在三维随机建模的基础上，把整个储层分为若干网格，视每一个网格上的储量参数为随机变量，对于每一组随机变量，利用容积法进行储量运算后再进行网格积分，从而得到储量的一系列实现值。然后根据储量的分布作密度函数曲线和累计概率曲线，便可获得不同可信度的储量值。该方法既紧密结合了气藏的地质模型，又得到了不同可靠程度的储量数据，使储量结果更为客观。随机建模法计算所得的概率储量P_(90)为470.71×10~8m~3，与复算储量相差不大，误差为1.5％。在储量复算的基础上，依据储层分类和电阻率高低并结合测试产能对储量进行了分类与评价，Ⅰ类储量186.37×10~8m~3，占总复算储量的40％，无阻流量在5×10~4m~3以上；Ⅱ类储量183.33×10~8m~3，占总复算储量的39％，无阻流量在2×10~4m~3以上；Ⅲ类储量97.23×10~8m~3，占总复算储量的21％，属低效储量。除JS_2~1气层外，其他三层的Ⅰ、Ⅱ类储量共288.45×10~8m~3，均已动用。
(4)气藏综合调整方案研究：通过对沙溪庙组JS_2气藏开发方案的实施情况及开发效果来看，无论是地质认识还是开发层系及开发井网的确定、单井配产及生产规模的设计基本上符合气藏的实际情况，但因生产规模一直高于方案设计而造成稳产期缩短。气藏目前面临的主要问题是，一方面稳产困难，另一方面采出程度低，未动用储量数量大。剩余储量研究结果表明，气藏目前的剩余储量大，由两部分组成，一部分为低效储量，因没有生产井控制而未能动用，各气层均有分布，但主要分布在JS_2~1，JS_2~3气层；另一部分为相对优质储量，虽然已经动用，但因与生产井井距较大，依然保持了较高的地层压力。因而，气藏的稳产可以从两方面着手，其一是利用多层(双层或三层)压裂技术，纵向上动用低效储量，使之与相对优质储量合采；其二是部署调整井(含挖潜井)以提高可动用储量的采出程度，新增动用储量和新增可采储量将为气藏的继续稳产提供储量基础。针对不同类别探明储量及剩余储量的分布状况，部署调整井66口，设计调整方案3套，方案1不增加新井并对现有老井降产40×10~8m~3，使之平均日产量在240×10~4 m~3左右；方案2在方案1的基础上补充31口新井；方案3在方案2的基础上再补充35口新井。利用Eclipse数模软件在历史拟合的基础上，对各套方案的开发指标进行了动态预测，结果表明，增加新井后，气藏的累计采气量和采出程度明显增加和提高，方案3比方案2更优。通过66口调整井的实施，采气量增加32.7×10~8m~3(其中8.91×10~8m~3来自于JS_2~1、JS_2~3)，采出程度提高6.5％，气藏的稳产期延长5年，推荐方案3作为JS_2气藏的调整方案。
本文研究中的创新点为：
1、首次采用随机建模法对JS_2多层致密气藏的储量进行了计算。该方法不但体现了容积法储量计算中的地质概念，又充分考虑了储量计算参数的不确定性，融积分法与统计模拟法于一体；计算结果用概率的方式表达，在一定程度上规避了常规方法只获得一个储量值而不能对这一储量的准确性进行评估的缺陷。
2、首次针对多层致密气藏提出了经济与次经济储量并举、通过多层压裂技术和调整井的实施达到经济储量带动次经济储量的立体开发及调整思路。根据这一思路编制了JS_2气藏的立体开发调整方案，这对过去只注重于经济储量动用的大中型多层叠置气田的高效开发具有重要的指导和借鉴意义。
3、将现代油气藏管理的两大技术手段—储层建模和数值模拟融为一体，用于多层致密气藏立体开发调整方案研究之中。形成了一套以储层精细地质模型为基础，以储层和储量的定量评价为目标，以剩余气分布研究为核心的致密气藏开发调整方案研究技术体系。
Tight sandstone gas reservoir is of low richness, low porosity, low permeabilityand low individual well producing rate, however, it produced natural gas in a largeproportion in our country. At present, how to exploit efficiently the large multi-layerssuperimposed tight sandstone gas reservoir is still in the preliminary stage in theworld, and don't even mention the research on the three-dimensional adjusteddevelopment plan. The Xin Chang gas field, which located at the middle section ofthe western Sichuan depression in the west part of Sichuan basin, is a large tightclastic gas field imposed by many gas reservoirs vertically. Its production lies in thetop list in our country. JS_2 reservoir, the main producing reservoir and consisting fourgas formations, produced in 2000, achieved the designed production in 2002 and ithad been producing over the designed for almost six years. Now it is difficulty toproduce steadily, so, now, the proper & timely adjustment for the gas reservoir is ourfirst target.
Based on the various geologic formation, experimental, geophysical and dynamicdata, adopted by the methods of static prediction with dynamic analysis, used by themeasures of three-dimension geological modeling and numerical simulation, JS_2 gasreservoir has been quantitatively key researched on the unproduced gas distributionwith the goal of quantitative evaluation, which aims to improve the recovery andeconomic efficiency and to provide the direct & efficient guide for the furtherdevelopment.
During the process of development, more and more data & knowledge achievedand more advanced fracturing technology results in the even less steering function tothe reservoir development for the original plan. That is why this article focuses on theissues as following:
(1) Basic features description of gas reservoir
The fine description of structural characteristics, sedimentary microfacies andsand body spread based on the 200 wells log and the seismic data, indicates that JS_2 isa flat nose structure, the main sedimentary microfacies are distributary river course ofdelta plain with four thick & stable sand bodies. A large amount of chlorite and calcite presented and their uneven distribution lead to worse physical properties and strongmicro non-homogeneous property by the description of reservoir lithology, physicalproperty, diagenesis and non-homogeneous property. The comprehensive analysis onthe water produced wells shows that formation water exits in the formation edge andwithout unified boundary between gas and water. There are obvious characteristicsreflected on the log curve and seismic data, such as low natural gamma ray, lowneutron, low density, high sonic and medium resistivity, which can distinguish thereserves, low frequency, strong amplitude and low resistance, whose gas -bearingresponse module can give the plane prediction to the reserve. From the above researchwork, it is concluded that JS_2 is a kind of porous tight gas reservoir with abnormalhigh pressure, driven by gas and controlled by structure and lithology.
(2) Three-dimension modeling of gas reservoir
Based on the comprehensive description above mentioned, according to thegeological statistics theory, adopted by modeling software Petrel and under the controlof function, we simulated 100 actualizations and selected the final module whichhas the best conformity with geological knowledge. Besides, used by the method ofrandom modeling and under the control of petrofacies module, we simulated 100realizations individually for five parameters including porosity, permeability watersaturation, sonic and resistivity, and also selected the final actualization as the finalmodules which have the best conformity with facts. In accordance with the obtainedparameter module, combined with the characteristics of various gas formation, weset down the classification criteria of reserve and at the same time, we made anevaluation as listed: on the range of research area,ⅠandⅡreserves dominate in JS_2~2and JS_2~4 reservoirs, JS_2~3 withⅢreserve andⅠandⅡreserves local distributed andJS_2~1 withⅠandⅡreserves of worse quality.
(3) Reserves recalculation and evaluation
Reserves recalculated by using the volumetric method and the stochasticmodeling method in this paper. Based on the original proved reserves and accordingto the abundant dynamic and static datum, each parameter in the volumetric method isrecalculated and confirmed by using the new interpretation model. It is obtained thatthe reserves of Sha Xi Miao reservoir (JS_2) is 463.75×10~8m~3 through the volumetricmethod, and the reserves of each layer (JS_2~1, JS_2~2, JS_2~3, JS_2~4) is respectively104.85×10~8m~3, 167.75×10~8m~3, 46.56×10~8m~3, 144.60×10~8m~3. The recalculatedreserves has decreased by 71.60×10~8m~3 compared with the original proved reserves which is 534.35×10~8m~3. The layers of decreased reserves are JS_2~3, JS_2~4, the reason isthe decreasing of area. The stochastic modeling method is based on thethree-dimensional stochastic modeling, through dividing the whole reserves layer intoa lot of grids, considering the reserves parameters in each grid as stochastic variables, and performing grid integral for each group of stochastic variables after reservescalculation by the volumetric method, and a series of realized values of reserves arefinally figured out. Then reserves datum of different reliability can be obtained bydrawing the density function curves and accumulative probability curves according tothe distributing of reserves. This method is not only combined with geologic modelclosely, but also reserves datum of different reliability is obtained, which makingresults more external. The probability reserves P_(90) is 470.71×10~8m~3 through thestochastic modeling method. The value is close to that of recalculated reserves and theerror is 1.5%. Based on the reserves recalculation, reserves is classified and evaluatedaccording to layer-sorting, resistivity-sizing, and testing productivity. Reserves ofgradeⅠis 186.37×10~8m~3, which is 40% of the total, and AOF is more than 5×10~4m~3.Reserves of gradeⅡis 183.33×10~8m~3, which is 39% of the total, and AOF is morethan 2×10~4m~3. Reserves of gradeⅢis 97.23×10~8m~3, which is 21% of the total andbelongs to low- profit reserves. Except JS_2~1, reserves of gradeⅠandⅡof other layershave been produced which is totally 288.45×10~8m~3.
(4) Synthetic adjustment plan research of gas reservoir
According to the execution schedule and development effect of the developmentplan of Sha Xi Miao JS_2 reservoir, not only geologic cognition but also developmentlayer series, well pattern, product of single well, and production scale are accord withthe practice of reservoir. But the production scale is always higher than the designedscale, which results in that the stable production period has been shortened. The mainproblems the reservoir faced are that it is difficult to keep production stable, on theother hand, recovery percent of reserves is rather low and un-produced reserves israther great. Remained reserves research shows that the present remained reserves ofreservoir is great which is composed of two parts. One is low- profit reservesdistributing in every layer but mainly in JS_2~1, JS_2~3, which can not be produced due tohave no well controlling. The other is relatively high grade reserves which keepsrather high formation pressure due to big well spacing although has been produced.Thus there are two ways to keep production stable. One is to use commingledproducing wells between low- profit and high grade reserves through multi-layer fracturing technology, the other is to dispose adjustment wells (including wellwork-over) to increase recovery percent of producible reserves. Newly-increasedproduced reserves and producible reserves will provide keeping production stablewith substantial bases. According to the distribution of different grade of reserves andremained reserves, 66 adjustment wells are disposed and three adjustment programsare designed. The first program decrease present wells production by 45×10~4m~3without adding new wells and makes daily production to the level of 240×10~4m~3. Thesecond program adds 31 new wells on the base of the first program. The thirdprogram adds 35 new wells again on the base of the second one. The dynamicdevelopment indexes of each programs have been forecasted by using ECLIPSEsoftware based on history matching. The results show that the cumulative productionand recovery percent is obviously increased and the third program is better than thesecond one. Through disposing 66 adjustment wells, the production is increased by32.7×10~8m~3 (8.91×10~8m~3 from JS_2~1 and JS_2~3), the recovery percent is increased by6.5%, and the stable production period is extended by 5years. Thus the third programis recommended to be the adjustment paln of the reservoir.
This paper has three innovative points:
1. The reserves of multi-layer tight reservoir JS_2 is calculated by using stochasticmodeling method for the first time. This method combines integral method withstatistical simulation, which not only exhibits geologic conceptions in the volumetricmethod, but also considers the uncertainty of calculative parameters of reserves. Theresults is expressed by the way of probability, and to some degree, evades thelimitation that traditional methods can only obtain one reserves value but evaluate theveracity of the value.
2. Economic reserves and hypo-economic reserves are both considered aimed atmulti-layer tight gas reservoir. The method of three-dimensional Adjustment Plan forhypo-economic reserves being driven by economic reserves by multi-layer fracturingand implementing of adjustment wells. According to this idea, the three-dimensionalAdjustment Plan has been drawn. It has important direction and reference significanceto high-efficient development of large and middle scale gas fields, only the economicreserves of which are produced in the past.
3. The two technologies of modern reservoir management-reservoir layermodeling and numerical model combine to one part, which is used to researchthree-dimensional Adjustment Plan of multi-layer reservoir. A researching technology system for tight reservoir Adjustment Plan has been formed, which is based on thefine geologic model, making a target of quantitative evaluation for reservoir layersand reserves, and taking the distribution of remaining gas as the researching point.
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