Seventeenth SPE Improved Oil Recovery Symposium

　　April 24-28 2010

　　Renaissance Hotel, Tulsa, Oklahoma

　　SPE 129965

　　Application of the Multiwell Productivity Index-Based Method to Evaluate Interwell Connectivity

　　D. Kaviani, SPE, U. of Calgary; P.P. Valkó, SPE, Texas A&M U.; and J.L. Jensen, SPE, U. of Calgary

　　Numerous studies have concluded that connectivity is one of the most important factors controlling success of improved oil recovery processes. Interwell connectivity evaluation can help identify flow barriers and conduits and provide tools for reservoir management and production optimization. The multiwell productivity index (MPI)-based method provides the connectivity indices between well pairs based on injection/production data. By decoupling the effects of well locations, skin factors, injection rates, and the producers’ bottomhole pressures from the calculated connectivity, the heterogeneity matrix obtained by this method solely represents the heterogeneity and possible anisotropy of the formation. Previously, the MPI method was developed for bounded reservoirs with limited numbers of wells. In this paper, we extend the MPI method to deal with cases of large numbers of wells and open reservoirs. To handle open reservoirs, we applied some modifications to the MPI method by adding a virtual well to the system and by modifying the pore volume. We applied the modifications in two nonvolumetric systems where there was either a leaking zone or an isolated zone, and found the approaches using the virtual well could predict the reservoir performance accurately. In cases with large numbers of wells, the required computational time to calculate the heterogeneity matrix may make the problem intractable. Therefore, we applied a model reduction strategy based on the location of the wells, called windowing. This technique ignores the parameters that have smaller effects on reservoir performance. We applied windowing to two cases with large numbers of wells (16 and 41 wells). We observed that, by selecting the proper window size, we can predict the reservoir performance accurately (R2 values greater than 99%) and decrease the CPU time up to a factor of 20 for the studied cases. The approaches described enabled us to provide realistic interpretations of interwell connectivity for complex cases where the simple MPI method would be difficult to apply. Integration of these approaches with the MPI method can quickly and efficiently model field data to optimize well patterns and flood parameters.

　　大量研究已經(jīng)證實(shí)，連通度是影響提高原油采收率的最重要的因素之一。評(píng)價(jià)井間連通度有助于識(shí)別原油流動(dòng)隔層和原油流動(dòng)管道，為油藏管理和開(kāi)采最優(yōu)化提供了手段。基于多井生產(chǎn)指數(shù)(MPI)的方法提供了基于注水/生產(chǎn)數(shù)據(jù)的井對(duì)之間的連通度指數(shù)。通過(guò)消除井眼位置、表皮系數(shù)、注水率、計(jì)算的連通度得出的井底壓力等因素的影響，這樣得到的非均勻性模型就可反映地層的非均勻性和各向異性。以前，針對(duì)封閉儲(chǔ)層根據(jù)少數(shù)井的數(shù)據(jù)就得出多井生產(chǎn)指數(shù)(MPI)。本文中，我們擴(kuò)展了MPI方法，處理了數(shù)目很多的井和不封閉油層。為了處理不封閉油層數(shù)據(jù)，我們通過(guò)把一個(gè)模擬井加入系統(tǒng)并修改孔隙體積，對(duì)MPI方法作了修正。我們?cè)谝词锹┦^(qū)或者是封閉區(qū)的兩個(gè)沒(méi)有測(cè)定體積的系統(tǒng)應(yīng)用這一修正，發(fā)現(xiàn)使用了虛擬井的方法能夠精確預(yù)測(cè)油藏特性。在數(shù)目很多的井的實(shí)例中，通過(guò)調(diào)整計(jì)算非均勻性所要求的計(jì)算次數(shù)可以解決難以處理的問(wèn)題。因此，我們應(yīng)用了一個(gè)基于井眼位置的模型規(guī)約策略，叫做開(kāi)窗術(shù)。這個(gè)方法忽略了對(duì)油藏特性影響小的參數(shù)。我們把開(kāi)窗術(shù)應(yīng)用于數(shù)目很多的井(16口井和41口井)的兩個(gè)實(shí)例。針對(duì)所研究的實(shí)例，通過(guò)選擇合適的油井最佳工作范圍，我們就可精確地預(yù)測(cè)油藏性能，降低計(jì)算機(jī)處理時(shí)間。相對(duì)于簡(jiǎn)單的MPI方法很難應(yīng)用的復(fù)雜實(shí)例，上述方法使我們能夠逼真地解釋井間連通度。綜合使用MPI方法能夠快速和有效地模擬現(xiàn)場(chǎng)數(shù)據(jù)，優(yōu)化井網(wǎng)及注水參數(shù)。

　　譯自 SPE 129965 第17次SPE提高原油采收率座談會(huì)