Reservoir-Surveillance Data Creates Value in Fractured-Carbonate Applications
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Determination of the value of information (VOI) is a well-known process for justifying data acquisition, but engineers struggle to extract relevant information from historical data to apply a Bayesian approach. The objective of this paper is to illustrate a methodology for identifying the VOI in reservoir management—in particular, for deriving the conditional probabilities of success when new and imperfect data are acquired.
Managers tend to avoid costs and production losses related to data acquisition. Pressure and rate transient analyses (PTA and RTA) along extended production time allow reservoir characterization and understanding of near-wellbore characteristics; however, PTA and RTA alone do not provide pressure- and fluid-distribution prediction beyond the wellbore. Such a task requires integration with reservoir simulation.
The Role of Surveillance in Integrated Reservoir Management (IRM)
IRM defines the supervision of activities designed to manage subsurface hydrocarbon reservoirs. IRM frameworks have been deployed across assets around the world to ensure that reservoir-management goals are achieved or exceeded.
IRM has been proved to help (a) shorten learning curves, hence reducing total cycle time, resulting in increased productivity for an asset; (b) measure key performance indicators that allow integration of the correct multidisciplinary efforts in delivering consistent results; and (c) foster a culture that challenges the status quo continually.
The role of surveillance in IRM is to improve the success and quality of reservoir-related activities (e.g., well work, rate control, and sustainable operations) continually while managing well integrity and concerns related to health, safety, and the environment (HSE) (e.g., manage the well-operating envelope and minimize HSE risk issues). To achieve consistent success, understanding reservoir performance and maintaining quality predictive models are paramount. These models are used to optimize well and reservoir performance continually (Fig. 1).
Reservoir Surveillance Guidelines (RSGs). The RSGs are corporate surveillance guidelines that set long-term business drivers and expectations for best practices; they establish the minimum requirements for surveillance per technology maturity and readiness. RSGs are delivered through a system that provides minimum requirements for consistent well-surveillance activities, enabled by VOI methodology, remote monitoring, and data-driven models. Among the goals of the RSGs are the following:
- Maintain reservoir performance and well behavior within the optimal operating envelope
- Avoid unnecessary trips to the wellsite
- Recognize and warn personnel of unsafe operations
- Determine and alert personnel of abnormal well-integrity conditions
The IRM system tracks adherence to RSGs; any deviation from the business plan will be recognized and justified at an annual reservoir-monitoring program for the asset. A plan will be developed to close such gaps.
Reservoir Strategic Surveillance Plan (RSSP). An RSSP is an asset-specific document that addresses the long-term objectives for the reservoir and establishes monitoring practices following the RSGs. Key to this practice is the use of the VOI methodology already well-known in the oil industry.
VOI. VOI analysis represents the value that can be added to a project if new data or information would provide a different outcome. The value of such information is increased if the ability of current models to predict the future is poor. Assuming an initial plan is optimal, if expected results are experienced, no further value can be obtained. However, if an unexpected performance is obtained, then the model can be reviewed and additional value pursued.
Any information-gathering opportunity must meet three criteria if it is to add value:
- Relevant—New information must offer the possibility of learning about this uncertainty.
- Material—Information has value only if it offers the potential to change decisions.
- Economic—Even if the information is relevant and material, it still has to be a good investment.
Surveillance Practices in Carbonate Reservoirs Under Waterflooding
Use of Tracer VOI. The injection of tracers is a well-established technique and an important tool for reservoir monitoring, used with other surveillance methods to assist reservoir management. It aids in understanding reservoir heterogeneity, reducing uncertainties linked to major faults, identifying pathways within the reservoir, monitoring water breakthrough, and obtaining a better tuning of reservoir simulation for forecasting.
Understanding Performance With Modern Analytical Techniques and Real-Time Data. The use of modern analytical techniques, along with surveillance data derived from real-time sources, has been preferred over the use of computationally intensive reservoir simulations. Although reservoir simulators provide a high level of analysis, they often cannot capture changes occurring at small scale, such as wellbore plugging, damage, and fracturing.
Various proposed analytical methods are associated with high-frequency long-term data from permanent downhole gauges (PDHGs). These methods help evaluate the performance of water injection and the behavior of production and injection ratios and the well-productivity index, follow the evolution of waterflooding, and assess the reservoir heterogeneities and uncertainties while taking remedial action without halting production.
Risk-Based Surveillance Planning. For optimal decision making, identifying the most-valuable VOI among the massive amount of surveillance data available is paramount because surveillance has a cost. The value of a surveillance plan can be complex to measure; moreover, conventional VOI techniques are not always appropriate because of the complexity of the data (multiple data decisions, multiple uncertainties). In a risk-based surveillance plan designed to evaluate all surveillance opportunities linked to the operational risk-management process, the many options are mapped against each risk, helping the user to quickly identify the surveillance that will add the most value.
Quantifying VOI With Ensemble Variance Analysis (EVA). The main goal of data acquisition is to improve reservoir management; however, data is expensive and uncertain at the time of the analysis. Therefore, one should identify and assess VOI from surveillance data in the early stages of development. One method to estimate VOI is to interrogate the possible reservoir-performance outcomes by analyzing multiple geological realizations with rigorous and expensive history-matching computations.
EVA quantifies the expected uncertainty reduction and the attainable VOI for a given surveillance plan more efficiently. EVA uses reservoir simulations with a multi-Gaussian assumption relationship between the measurement and the objective function, helping to reduce computational time and cost. The method can handle nonlinear forward models and arbitrary numbers of parameters. Even if the multi-Gaussian relationship does not apply, the EVA method still gives the most-conservative estimate of expected uncertainty reduction, providing a quick approach to estimate the VOI for a given surveillance plan. Still, the EVA method must overcome challenges such as the need for proper characterization and parameterization of uncertainty in the model, better error estimation, and the ability to handle more-advanced well strategies.
VOI Analysis: Case Studies
Two case studies are presented in the complete paper in which the VOI analysis helped compute the business cases for acquiring new reservoir-surveillance data using Bayesian probabilities. The first case addresses the justification for including real-time reservoir characterization (RTRC) while using underbalanced drilling (UBD). The second case deals with the surveillance benefit of using PDHGs. In the VOI analysis, it was shown that the value of conducting RTRC is $262 million/well, or 98 times the cost of the services. A decision was made to conduct horizontal well drilling with step-down trajectory using UBD supported with RTRC. Optimized well trajectories during drilling using RTRC provide unprecedented value in challenging carbonates with high heterogeneities and tight reservoir properties. The reliability of RTRC was a key success factor.
The VOI analysis of deploying and using PDHGs is $57.8 million/well, or 231 times the cost of the installation and services. A decision to install PDHGs in all carbonate wells under waterflooding and with high-permeability streaks is fully supported. Optimized production- and injection-rate controls guided by PDHG analysis provide additional value in the exploitation of carbonates with high heterogeneities. Again, the reliability of PDHG was a key success factor; even in worst-case conditions, the incremental value was still positive.
Reservoir-Surveillance Data Creates Value in Fractured-Carbonate Applications
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