集群式方案 簡化多勘探區(qū)開發(fā)-石油圈

集群式開發(fā)方案在大型油氣藏開發(fā)中將發(fā)揮重大作用！

編譯 | TOM 驚蟄

在多勘探區(qū)油氣藏中，如果開發(fā)商僅從經(jīng)濟(jì)學(xué)角度來證明每個(gè)勘探區(qū)開發(fā)的合理性，常常會(huì)使自己處于非常不利的位置。在集群式開發(fā)方法中，將不同探勘區(qū)之間的地質(zhì)相關(guān)性與勘探區(qū)的集群相結(jié)合，以確定開發(fā)的經(jīng)濟(jì)可行性。雖然方法很直觀，但對(duì)集群式開發(fā)的經(jīng)濟(jì)評(píng)估通常不考慮實(shí)際存在的地質(zhì)相關(guān)性以及開發(fā)的協(xié)同效應(yīng)。對(duì)這些協(xié)同效應(yīng)進(jìn)行建模分析，發(fā)現(xiàn)它們對(duì)油氣藏開發(fā)的經(jīng)濟(jì)評(píng)估具有顯著影響。

在評(píng)估不同勘探區(qū)之間相關(guān)性的經(jīng)濟(jì)影響時(shí)，必須將地質(zhì)勘探成果分解為共享要素與原位要素。所有相關(guān)勘探區(qū)之間共享的地質(zhì)要素稱為共享或油氣藏機(jī)會(huì)。在每個(gè)相關(guān)勘探區(qū)之間獨(dú)立地質(zhì)機(jī)會(huì)要素被稱為前景/成功率（PSR）。任何個(gè)體勘探區(qū)的地質(zhì)成功率將被定義為油氣藏機(jī)會(huì)乘以PSR。

在評(píng)估新區(qū)塊時(shí)，若該區(qū)塊地質(zhì)機(jī)會(huì)要素相關(guān)性占比較高，將有效地使完全獨(dú)立的要素?zé)o法發(fā)揮應(yīng)有的作用。從研究人員的油氣藏分析中可獲得關(guān)鍵信息，油氣藏開發(fā)存在最優(yōu)鉆井順序。對(duì)油氣藏機(jī)會(huì)影響最大的井，通常是首先開鉆的最優(yōu)井。行業(yè)慣例一般是側(cè)重于井的決策，而不是油氣藏的決策。因此，常規(guī)做法是首先鉆探地質(zhì)成功機(jī)會(huì)（Pg）最大或平均可采原油最多的井。而理想情況下，應(yīng)該鉆探油氣藏機(jī)會(huì)要素最多的勘探區(qū)。

地質(zhì)上的成功并非都是商業(yè)或是經(jīng)濟(jì)上的成功。為確定油氣藏能否可以進(jìn)行商業(yè)化開發(fā)，需經(jīng)過兩步流程。第一步是評(píng)估Pg機(jī)會(huì)，第二步是運(yùn)行現(xiàn)金流模型，以確定每個(gè)勘探區(qū)具有商業(yè)價(jià)值的油田最小規(guī)模（MCFS），假設(shè)獨(dú)立開發(fā)以及現(xiàn)有開發(fā)的集群式綁定。兩者的產(chǎn)物即為商業(yè)成功機(jī)會(huì)。將油氣藏視為個(gè)體勘探區(qū)或集群勘探區(qū)，將在決定商業(yè)化規(guī)模的閾值時(shí)，對(duì)決策產(chǎn)生重大影響。假設(shè)每個(gè)勘探區(qū)都可以用相同的現(xiàn)金流模型(勘探區(qū)到中央處理設(shè)備的距離相同)。

需要認(rèn)識(shí)到非常規(guī)油氣藏經(jīng)濟(jì)評(píng)價(jià)的主要因素，即開發(fā)決策，是基于平均項(xiàng)目產(chǎn)量，而不是單口井的產(chǎn)量。在油氣藏中，眾數(shù)或單口井最可能的產(chǎn)量（從頻率角度來看）通常是不具經(jīng)濟(jì)效益的。目前，正在開采的油氣藏都每口井的平均產(chǎn)量是具有商業(yè)價(jià)值的。隨著累計(jì)井?dāng)?shù)的增加，方差（P10與P90比率）降低，進(jìn)而趨于正態(tài)分布。

隨著累計(jì)井?dāng)?shù)的增加，對(duì)數(shù)正態(tài)分布的眾數(shù)逐漸轉(zhuǎn)變?yōu)槠骄鶖?shù)。在對(duì)數(shù)正態(tài)分布中，平均值將始終超過中值，始終大于眾數(shù)。在正態(tài)分布中，眾數(shù)等于中值，等于平均值。同樣的道理可以應(yīng)用到集群式開發(fā)新油藏的建模中。

為了說明集群開發(fā)方法對(duì)經(jīng)濟(jì)評(píng)估與決策過程的影響，研究人員提出了深水環(huán)境中三個(gè)勘探區(qū)的案例研究。在實(shí)際情況中，勘探區(qū)可能會(huì)有不同的油氣儲(chǔ)量分布與原位地質(zhì)機(jī)會(huì)因素。然而，在案例研究中假設(shè)所有勘探區(qū)的上述兩個(gè)參數(shù)都相同。這種簡化的目的是將重點(diǎn)放在過程上，而不是放在單個(gè)勘探區(qū)的細(xì)節(jié)上。同樣，案例研究不是僅限于深水環(huán)境，該過程適用于任何環(huán)境，無論是陸上還是海上。

雖然現(xiàn)金流模型會(huì)影響經(jīng)濟(jì)結(jié)果，但它被認(rèn)為獨(dú)立于本文提出的集群式開發(fā)的評(píng)估流程，并沒有在評(píng)估中凸顯作用。目前提出的評(píng)估流程將與其他財(cái)政制度合作，例如產(chǎn)量分享合同模式。

業(yè)內(nèi)的傳統(tǒng)方法是，一個(gè)新區(qū)域的評(píng)估是基于足以支持基礎(chǔ)設(shè)施建設(shè)的大發(fā)現(xiàn)。在不考慮地質(zhì)相關(guān)性影響的集群式開發(fā)的基礎(chǔ)上，做出開發(fā)決策的分析。集群式開發(fā)擁有地質(zhì)相關(guān)性的勘探區(qū)。然后，綜合考慮所有三個(gè)勘探區(qū)中可能的發(fā)現(xiàn)，制定開發(fā)決策。研究人員提倡第三種方法，下面將對(duì)此進(jìn)行討論。

具有共享油氣藏機(jī)會(huì)的集群式捆綁開發(fā)。研究人員認(rèn)為，深水案例是一個(gè)經(jīng)過驗(yàn)證的斷塊油氣藏，共享油氣藏機(jī)會(huì)占比高達(dá)80%。在經(jīng)濟(jì)性分析中，假定干井分析不能確定共享油氣藏機(jī)會(huì)系數(shù)，并對(duì)三個(gè)勘探區(qū)進(jìn)行鉆井。這種保守的案例研究方法是有意為之，因?yàn)樗钥勺C明，考慮共享油氣藏機(jī)會(huì)能夠?yàn)榻?jīng)濟(jì)分析增加價(jià)值。

對(duì)于擁有共享油氣藏機(jī)會(huì)的集群式捆綁開發(fā)方法，經(jīng)濟(jì)評(píng)估就類似于假定地質(zhì)獨(dú)立的勘探區(qū)所采用的方法。采用60000次迭代的蒙特卡洛計(jì)算法，同時(shí)考慮了勘探區(qū)之間的共享油氣藏機(jī)會(huì)，利用三種勘探區(qū)的地質(zhì)資源儲(chǔ)量分布模擬出可能的產(chǎn)量。

這需要一個(gè)九分支決策樹，而不是三個(gè)評(píng)估模型中用于第二個(gè)的八分支決策樹，來總結(jié)出模擬結(jié)果，因?yàn)闀?huì)有兩種不同的方式導(dǎo)致徹底失敗：油氣藏不存在，或者即使油氣藏存在，所有干井都是由原位勘探區(qū)地質(zhì)特征因素所引起的。

決策樹的主要結(jié)果顯示，多重發(fā)展的可能性現(xiàn)在為22.4％（與不考慮共享油氣藏機(jī)會(huì)時(shí)的19％相比）。此外，決策樹還顯示無法開發(fā)的可能性為63.3％（在不考慮共享油氣藏機(jī)會(huì)時(shí)略高于62.9％）。在對(duì)勘探區(qū)之間的地質(zhì)相關(guān)性進(jìn)行建模時(shí)，這些結(jié)果與預(yù)期結(jié)果一致。在一個(gè)勘探區(qū)中取得成功的好消息，將增加在另一個(gè)相關(guān)勘探區(qū)中取得成功的機(jī)會(huì)，從而增加多個(gè)開發(fā)的機(jī)會(huì)(并增加成功案例的油氣儲(chǔ)量)。然而，導(dǎo)致一個(gè)勘探區(qū)出現(xiàn)干井的壞消息，增加了其他相關(guān)勘探區(qū)出現(xiàn)干井的可能性，從而增加了該項(xiàng)目失敗的總機(jī)會(huì)。

由于具有開發(fā)價(jià)值的獨(dú)立勘探區(qū)規(guī)模的門檻較低，因此使用集群式開發(fā)，至少一個(gè)開發(fā)項(xiàng)目的概率已經(jīng)增加。在集群式開發(fā)的戰(zhàn)略下，多個(gè)開發(fā)項(xiàng)目的機(jī)會(huì)顯著增加?？紤]到共享油氣藏機(jī)會(huì)增加了成功案例中的開發(fā)數(shù)量，但由于地理上的相關(guān)性，會(huì)降低商業(yè)成功的機(jī)會(huì)。

當(dāng)放棄獨(dú)立策略時(shí)，平均開發(fā)數(shù)量、平均原油最終采收率以及平均DNCF設(shè)為8%，預(yù)期價(jià)值與成功案例指標(biāo)均有顯著改善。當(dāng)考慮到成功案例中開發(fā)的更多發(fā)現(xiàn)所帶來的共享油氣藏機(jī)會(huì)時(shí)，集群式開發(fā)方法也顯示出經(jīng)濟(jì)上的改善，而整體開發(fā)機(jī)會(huì)只減少了很小一部分。

In plays with multiple prospects, decision-makers put themselves at a significant disadvantage by using economics on a standalone basis to justify development for each prospect. In the clustered-development approach, the geologic dependence between prospects is combined with the aggregation of prospects to determine the economic viability of a grassroots development offshore. Although easily visualized, economic evaluations of clustered developments typically do not consider the geological dependencies and development synergies that exist. Modeling these synergies has a significant effect on the economic evaluation of developments.

Geologic Dependency

In assessing the economic effect of the dependencies between prospects, breaking the chance of geologic success into a shared element and a local element is mandatory. The geologic-chance elements shared between all related prospects will be referred to as either the shared or play chance. Those geologic-chance elements that are independent between each related prospect are referred to as the prospect/success ratio (PSR). The probability of geologic success for any individual prospect will be defined as the play chance multiplied by the PSR.

When evaluating a new region, having a high degree of dependence within the geologic chance-of-success components will effectively derisk the play relative to total independence. A key learning from the authors’ play analysis is that an optimal drill order always exists. The well that will have the largest effect on the play chance is typically the optimal well to drill first. Industry practice often is focused on a well decision rather than a play decision. Consequently, the well with the highest chance of geologic success (Pg) or the largest risked mean recoverable resources typically is drilled first. Ideally, prospects should be drilled in a location that best addresses the play-chance elements.

Effect of Aggregation on Size Dependency

Geological successes are not all commercial or economic successes. A two-step process is used to determine the chance of commercial success leading to a development. The first step is assessing the total chance of Pg. The second step is to run the cash-flow model to determine the minimum commercial field size (MCFS) for each prospect, assuming a standalone development and a clustered tie-in to an existing development. The product of the two is the chance of commercial success. Viewing a play as an individual prospect vs. as an aggregate of prospects will affect decision making materially in the determination of the size threshold for commercialization. An assumption has been made that each prospect can be represented by the same cash-flow model (i.e., the same distance from prospect to central processing facilities).

One of the major factors in economic assessment of unconventional plays has been the understanding that development decisions are based on the average program outcome, not on individual well outcomes. In resource plays, the mode or most-likely single-well outcome (from a frequency perspective) typically is uneconomical. Resource plays that are active today are those in which the program’s average per well mean outcome is economical. As the number of wells being aggregated increases, the variance (P10/P90 ratio) decreases and the distribution tends toward a normal distribution.

The mode of the log-normal shifts toward the mean as the number of wells being aggregated increases. In a log--normal distribution, the mean will always exceed the median, which will always exceed the mode. In a normal distribution, the mode equals the median, which equals the mean. This same understanding can be applied in modeling clustered developments in greenfield plays.

Case Study

To illustrate the effect of the clustered--development approach on the economic-evaluation and decision-making process, a case study of three prospects in a deepwater setting is presented in the complete paper. In practice, the prospects likely would have different resource--volume distributions and local geologic-chance factors. For the case study in this paper, however, both parameters are assumed to be the same for all prospects. This simplification is meant to keep the focus on the process rather than on the details of the individual prospects. Likewise, the case study is not defined beyond being in a deepwater setting because the process is applicable in any setting, onshore or offshore.

The cash-flow model used to generate the economics assumes a royalty and tax fiscal regime. While the cash-flow model will affect the economic results, it is considered to be independent of the process of evaluating clustered developments being presented in this paper and is not emphasized. The process being presented will work with other fiscal regimes, such as a production-sharing-contract model.

The traditional industry approach, in which a new region is evaluated on the basis of one discovery large enough to support the infrastructure development.

An analysis wherein the development decision is made on the basis of a clustered development with no consideration for the effect of geologic dependence.

A clustered development with geologic dependence between the prospects. The development decisions are then based on what might be found when all three prospects are considered. The authors advocate this third approach, and it is discussed next.

Clustered Tie-In Development Methodology With Shared Play Chance. The authors consider that the deepwater case study is in a play-segment extension of a proven play with a high shared play chance of 80% associated with migration risk. For economic analysis, the assumption is made that dry-hole analysis will be inconclusive of the shared play chance factor and all three prospects will be drilled. This conservative approach for the case study is adopted deliberately because it still will demonstrate that consideration for the shared play chance will add value to the economic analysis.

For the clustered tie-in development methodology with shared play chance, economic evaluation is similar to that adopted when prospects are assumed to be geologically independent. A Monte Carlo simulation with 60,000 iterations was used to simulate the possible outcomes using the prospect geologic-resources distributions of the three prospects but now also considering the shared play chance between prospects.

A nine-branch decision tree is needed this time, rather than the eight-branch decision tree used in the second of the three evaluation models, to summarize the simulation results because total failure can now happen in two separate ways: the play does not exist or all dry holes are caused by local prospect-specific factors even though the play exists.

The main results of the decision tree show that the chance of multiple developments is now 22.4% (compared with 19% when not considering the shared play chance). The decision tree also shows that the chance of no developments is 63.3% (slightly higher than 62.9% when not considering the shared play chance). These results are consistent with expected outcomes when modeling geologic dependencies between prospects. Good news leading to success in one prospect will increase the chance of success in the other dependent prospects, increasing the chance of multiple developments (and increasing the success-case resource volumes). However, bad news leading to a dry hole in one prospect increases the chance of a dry hole in the other dependent prospects, increasing the overall chance of failure for the program.

The probability of having at least one development has increased with the use of clustered development because of the lower threshold on individual prospect discovery sizes that can be developed. The chance of multiple developments has increased significantly with a clustered-development strategy. Considering the shared play chance increases the number of developments in the success case but reduces the chance of commercial success because of the geologic dependencies.

Significant improvement in expected-value and success-case metrics is seen for the mean number of developments, mean oil estimated ultimate recovery, and mean DNCF at 8% when the standalone strategy is abandoned. The clustered-development approach also shows economic improvement when considering shared play chance caused by a larger number of discoveries developed in the success cases with only a small reduction in the overall chance of development.

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