Unconventional petroleum resource plays present unique assessment challenges. These large, single accumulations cannot be counted and analysed as discrete entities that are delineated by down-dip water contacts. Equally important, the main assessment challenge relates to exploitation risks and uncertainties. This paper presents an integrated stochastic assessment framework for decisions related to shale gas resource plays. The shale gas resource play is modelled as a set of discrete cells that have not been explored (exploited) and that have the potential for economic production. The distinctive aspect of the modelling tool is the use of stochastic simulation to calculate the risks of failure in either the exploration, the appraisal/pilot, or the exploitation phases of the project on the basis of both sub-surface uncertainties and above-surface activity performance, cost and duration uncertainties. The tool also generates stochastic performance metrics that capture alternative outcome scenarios, economic returns and the delivery schedule of production and reserves. The performance metrics support both project-level and portfolio-level decisions related to unconventional resource plays. Project-level application is illustrated using data from a Canadian shale gas resource play. Introduction Unconventional petroleum assets are large single accumulations. They form a geologically diverse group, but include coal-bed methane (CBM), tight gas and fractured shale gas. All unconventional petroleum assets share some important characteristics: they are often very large accumulations, many of the largest accumulations are known in the sense that we know where they are: The assets cannot be counted and analysed as discrete entities that are delineated by down-dip water contacts (Schmoker, 1999) as are conventional accumulations and fields. They are therefore also frequently referred to as continuous accumulations. Unconventional petroleum assets present unique assessment challenges. Estimates of in-place resources are not very useful as recovery is key. Exploration is more like appraisal, where the key decision is made after doing a pilot test production that can prove the potential for commercial production. Commercial production is often an issue of investing in innovations that can facilitate effective, manufacturing-style exploitation where scale is key. And the key to commercial success is identification and exploitation of what are potentially unevenly distributed and sparse number of sweet spots. Referring to the localization of sweet spots in coal based methane plays, Donovan (2001) states "75% of the production in the San Juan Basin comes from 35% of the wells on 5% of the acreage". This paper presents the application of a framework for integrated risk resource and economic value assessment of unconventional petroleum assets (Stabell, 2005) that has been applied to shale gas plays. The illustrative example is from a potential Canadian shale gas play. The analysis framework builds on the FORSPAN model developed by the USGS (Schmoker, 1999, 2002). FORSPAN is a stochastic geology- and engineering-based model for assessment of the petroleum resources that can be recovered in a finite forecast span (FORecast SPAN) from continuous (unconventional) petroleum accumulations. Each continuous petroleum accumulation is viewed as composed of a set of discrete cells that have not been explored (exploited) and that have the potential for economic production. Each cell is the drainage area of a well. Assuming uniform well spacing, then draining area and well spacing are synonymous model parameters. Recoverable volumes can vary between cells, with some cells being non-commercial. One of the key elements in the framework is that it includes modelling of the activities and economics of exploring and exploiting the resource play with explicit attention to costs, durations and production in order to generate after-tax cash flow profiles. Another important element is the use of the sweet spot as the analytical unit of analysis for both the assessment of the potential resources in the unconventional asset and the modeling of how the asset is explored and exploited. A sweet spot is a collection of cells where production characteristics are particularly favorable. The shorthand notation for the integrative framework is therefore also "SWEETR", for "SWEET spot Resources" (Stabell, 2005).

No abstract

Unconventional shale wells involve dynamic flow environments, which can be challenging to artificial lift systems required to produce these wells. Early-stage production from these wells is characterized by rapid production declines. Additionally, these wells experience significant production rate and phase fluctuations. Gas lift is a method of choice for producing gas-dominant assets, and it is commonly used early in the life cycle of liquid-dominant assets when production rates are higher. The design, the operation, and the general production management for shale wells requires a completely different approach and mindset than for conventional wells.Production systems analysis, usually referred to as nodal analysis, is a design and optimization technique used to evaluate a variety of current and future production scenarios under the assumption of steady state. Well test data, downhole gradient surveys, or production logging surveys are periodically sampled and provided as boundary conditions for the production systems analysis. The future reservoir conditions, typically obtained from reservoir simulations, are also used as boundary conditions. After performing the systems analysis, operators validate outcomes and determine the correct actions to take by using sporadic measurements. Operators are recognizing that the lower measurement frequency and resulting slower and offline analysis techniques provide incomplete, if not inaccurate, snapshots of the dynamic production environments of shale assets. To address that situation, several operators have started deploying downhole pressure/temperature gauges to understand and manage dynamic production behavior. There is a need for dynamic production modeling tools that analyze field conditions with realtime data and that provide real-time suggestions for corrective production improvement. This paper presents a dynamic production analysis methodology using real-time downhole measurements and its implementation in a software tool.The presentation provides results from two shale wells produced using gas-lift technology in a Permian asset. Both wells are instrumented with permanent electronic downhole gauges below the operating orifice valve to measure pressure and temperature in the casing-tubing annulus and in the tubing. The real-time data from gauges is visualized and analyzed in real time to diagnose artificial lift performance, including gas-lift valve behavior. More importantly, the analysis-inferred reservoir static pressure and instantaneous productivity index can be compared to the numerical reservoir simulations.Real-time downhole data coupled to dynamic production analysis is presented for the first time. This approach leads to more accurate production forecasting as well as optimization of highly dynamic shale wells.