The Value of Reservoir Surveillance - Applications to Fractured Carbonates Under Waterflooding

Abstract

As reservoirs mature, subsurface flow complexity and surface production operation challenges increase. This brings the necessity of making capital-intensive decisions to sustain or increase reservoir potential in an optimum way. However, subsurface uncertainties affect decision success. Reservoir surveillance, a process that involves data acquisition, validation, analysis, integration opportunity generation and execution, can mitigate the outcome of such decisions in the presence of uncertainties. Although Value of Information (VOI) is a well-known process for justifying data acquisition, engineers struggle to extract the relevant information from historical data to apply Bayesian approach. The objective of this paper is to illustrate a methodology for identifying the value of information in reservoir management, in particular for deriving the conditional probabilities of success when new and imperfect data are acquired. A methodology to assess the value of reservoir surveillance is supported by two cases. In the first case, the incremental value of Real-Time Reservoir Characterization (RTRC) in underbalanced drilling (UBD) was nearly 100 times the cost of the services; in the second case, the incremental value of permananet downhole gauges (PDHG) was near 230 times the cost of installation and services. Reliability of facquired data, among other uncertainties, resulted to be a key success factor for both cases; however, in worst-case conditions, the incremental value was always positive.

Rapid Identification of Interwell Fracture-Cavity Combination Structure in Fracture-Cavity Reservoir Based on Tracer-Curve Morphological Characteristics

“…The main methods to improve oil recovery from fracture-cavity reservoirs have become water injection of a single well to replace oil, water injection of a fracture-vuggy unit to drive oil, nitrogen injection, foam flooding, and other development methods fracture-cavity (Farhadinia et al, 2011;Lyu et al, 2017;Su et al, 2017;Yue et al, 2018a;Hou et al, 2018;Sheng et al, 2019;Zheng et al, 2019). With the expanded development of fracture-cavity reservoirs, the identification of fractures and caverns has shifted from macroscopical division of fracturecavity units to detailed identification and characterization of interwell fracture-cavity composite structures to meet the needs of water/gas injection formulation, flow-channel adjustment, and other programs for tapping potential (Trice and C Reservoirs Ltd, 2005;Dittaro et al, 2007;Shbair et al, 2017;Alaa et al, 2018).…”

“…The characteristics of fracture-cavity reservoirs can be revealed by various monitoring data acquired from different angles, but the degree of reflection is variable, and these monitoring techniques often have certain limitations. Common monitoring data used to identify fractures or cavities, such as seismic, coring, conventional logging, image logging, drilling, and well testing, show large-scale and lowresolution results, or they only show results near a single well (Dittaro et al, 2007;Corbett et al, 2010;Wang et al, 2013;Shbair et al, 2017;Alaa et al, 2018;Wan et al, 2018;Lai et al, 2019;Tian et al, 2019;Wei et al, 2019). Dynamic production data can only be used to analyze interwell connectivity, and it is difficult to identify interwell fracture-cavity composite structures (Gazi et al, 2012;Zhao, 2017;Al-Obathani et al, 2018;Yue et al, 2018b).…”

Fuzzy logic applied to value of information assessment in oil and gas projects

“…Grose and Smalley developed a risk-based surveillance planning method based on a value of information approach for data acquisition in producing fields (2017). Shabair et al (2017) discussed a practical implementation of value of information applied to a reservoir surveillance plan for a fractured carbonate under waterflooding. Similarly, Clemen (1996) and Suslick and Schiozer (2004) discussed applications and methods which enrich the VOI process.…”