石油与天然气地质
石油與天然氣地質
석유여천연기지질
OIL & GAS GEOLOGY
2014年
4期
556-561
,共6页
三维地震反演%产能指标预测%砂砾岩油藏%准噶尔盆地西北缘
三維地震反縯%產能指標預測%砂礫巖油藏%準噶爾盆地西北緣
삼유지진반연%산능지표예측%사력암유장%준갈이분지서북연
3D seismic inversion%productivity index prediction%coarse-grained clastic reservoir%northwestern margin of Junggar Basin
为了利用三维地震资料开展冲积扇低孔、低渗砂砾岩油藏产能指标预测研究,选取准噶尔盆地西北缘Y地区三叠系百口泉组油藏为靶区,在砂砾岩厚度与孔隙度等常规储层预测基础上,精细剖析影响油藏产能的渗透性和含油性等因素,将老区初期平均月产量数据引入三维地震反演过程中,采用层层深入、逐步逼近的思路开展油藏产能指标预测研究,总结形成了“特征曲线反演找准砂砾岩、孔隙度反演找准高物性砂砾岩、自然电位反演找准渗透性砂砾岩、电阻率反演找准含油砂砾岩、多体融合预测油藏产能指标”的研究流程。最终以月产能指标为硬数据,以波阻抗、孔隙度、电阻率和自然电位反演数据体及时间域构造为训练样本,利用神经网络模拟得到油藏产能指标数据体。研究结果表明,预测月产能指标与油井初期平均月产油量为正相关,相关系数R2=0.9487,老井初期平均月产量大于300 t的预测误差小于10%。产能指标数据体蕴含岩性、物性、含油性和渗透性等控制油气分布的多种信息,依据Y地区相应研究成果建议部署的3口评价井试油产量均在5t/d以上,验证了该产能指标预测技术的准确性与实用性。
為瞭利用三維地震資料開展遲積扇低孔、低滲砂礫巖油藏產能指標預測研究,選取準噶爾盆地西北緣Y地區三疊繫百口泉組油藏為靶區,在砂礫巖厚度與孔隙度等常規儲層預測基礎上,精細剖析影響油藏產能的滲透性和含油性等因素,將老區初期平均月產量數據引入三維地震反縯過程中,採用層層深入、逐步逼近的思路開展油藏產能指標預測研究,總結形成瞭“特徵麯線反縯找準砂礫巖、孔隙度反縯找準高物性砂礫巖、自然電位反縯找準滲透性砂礫巖、電阻率反縯找準含油砂礫巖、多體融閤預測油藏產能指標”的研究流程。最終以月產能指標為硬數據,以波阻抗、孔隙度、電阻率和自然電位反縯數據體及時間域構造為訓練樣本,利用神經網絡模擬得到油藏產能指標數據體。研究結果錶明,預測月產能指標與油井初期平均月產油量為正相關,相關繫數R2=0.9487,老井初期平均月產量大于300 t的預測誤差小于10%。產能指標數據體蘊含巖性、物性、含油性和滲透性等控製油氣分佈的多種信息,依據Y地區相應研究成果建議部署的3口評價井試油產量均在5t/d以上,驗證瞭該產能指標預測技術的準確性與實用性。
위료이용삼유지진자료개전충적선저공、저삼사력암유장산능지표예측연구,선취준갈이분지서북연Y지구삼첩계백구천조유장위파구,재사력암후도여공극도등상규저층예측기출상,정세부석영향유장산능적삼투성화함유성등인소,장로구초기평균월산량수거인입삼유지진반연과정중,채용층층심입、축보핍근적사로개전유장산능지표예측연구,총결형성료“특정곡선반연조준사력암、공극도반연조준고물성사력암、자연전위반연조준삼투성사력암、전조솔반연조준함유사력암、다체융합예측유장산능지표”적연구류정。최종이월산능지표위경수거,이파조항、공극도、전조솔화자연전위반연수거체급시간역구조위훈련양본,이용신경망락모의득도유장산능지표수거체。연구결과표명,예측월산능지표여유정초기평균월산유량위정상관,상관계수R2=0.9487,로정초기평균월산량대우300 t적예측오차소우10%。산능지표수거체온함암성、물성、함유성화삼투성등공제유기분포적다충신식,의거Y지구상응연구성과건의부서적3구평개정시유산량균재5t/d이상,험증료해산능지표예측기술적준학성여실용성。
In order to use 3D seismic data for productivity index prediction of alluvial fan coarse-grained clastic reservoirs with low porosity and low permeability , we chose the Triassic Baikouquan Formation reservoir in Y-region at the north-western margin of Junggar Basin as a case .Based on traditional reservoir prediction such as thickness and porosity of coarse-grained clastic reservoirs ,we analyzed in detail factors influencing permeability and oil-bearing properties ,and in-troduced the average monthly production data at the early stage of development into 3D seismic inversion to predict the productivity index .The following work flow was established:‘finding coarse-grained clastic reservoirs through typical curve inversion ,finding high quality coarse-grained clastic reservoirs through porosity inversion ,finding permeable coarse-grained clastic reservoirs through spontaneous potential inversion , finding oil-bearing coarse-grained clastic reservoirs through resistivity inversion ,and predicting reservoir productivity index with the combination of several methods ’ .A pro-ductivity index cube was finally generated through Neural Network modeling by using the monthly productivity as hard da -ta and wave impedance,porosity,resistivity,spontaneous potential inversion data cube and time domain structure as trai-ning samples.The result shows that there is a positive correlation (R2 =0.948 7)between the predicted monthly produc-tivity and initial average monthly production .For wells with an initial monthly average production more than 300 ton,the error of prediction is less than 10%.The data cube contains various information controlling hydrocarbon distribution ,such as lithology ,reservoir property ,oil-bearing property and permeability .The oil production of three appraisal wells deployed based on this research in Y-region reached more than 5 ton per day,which verified the accuracy and practicability of this productivity index prediction technology .