Increased Net to Gross Ratio as the Result of an Advanced Well Placement Process Utilizing Real-Time Density Images

Abstract

Development drilling operations in the Zuluf Field / Khafji Reservoir (offshore Saudi Arabia) involve targets near the flanks of the main structure, where oil-filled sands are sandwiched between overlying gas and underlying water. Horizontal well technology is utilized to increase the reservoir footprint. This article relays recent geosteering examples in the Khafji Sand bodies. Demonstrated results show significant gains in well productivity through an advanced well placement procedure relying on real-time geosteering. An asset team implemented a process of well placement in order to maximize the reservoir contact while drilling1. The process involves continuous exchange of information between the well site and the office-based teams to allow fast and informed decisions. The success of the well placement process has been enhanced by preparation prior to drilling, continuous interpretation of the real time data while drilling and integrated teamwork throughout the project. A key technology in the well placement process is the use of realtime borehole density images in addition to the standard LWD data. Continuous interpretation of the image data (providing bed dip and thickness) and correlation of the LWD data, with the offset well data and geological models, provided the information necessary to maximize the reservoir contact "net pay" along the horizontal lateral section. A series of wells have been drilled using the advanced well placement process. Examples illustrate how real time interpretation of the data by the team increased the net to gross ratio from 35% to 50%. The resultant increase in production demonstrates the value and the necessity of the process in the ongoing development of the field. Introduction The Zuluf field is located in the Arabian Gulf, approximately 149 miles (240 kilometers) north of Dhahran, Saudi Arabia, in an average water depth of 118 feet. Discovery of the field was made in 1965 and 270 wells have been drilled to date. The Khafji Reservoir is part of the Khafji Member of the Middle Cretaceous, Wasia Formation. The Khafji Member conformably overlies the Lower Cretaceous, Shu'aiba Formation and in turn is conformably overlain by the Safaniya Member. The Khafji reservoir in the Zuluf field consists of a thick sequence of quartz-rich sandstones, siltstones, shales and various types of ironstones (siderite, chamosite, and glauconite). Minor amounts of limestone and a few coal beds are also present. The average reservoir porosity is 30 percent and average permeability is greater than 1 Darcy. The Khafji reservoir was deposited in a fluvial-dominated delta system which prograded over the shallow marine carbonate platform of the Shu'aiba Formation. The Khafji Member ranges from 625 to 875 feet in thickness and is subdivided into four major stratigraphic units (figure 1). The uppermost unit, the "Upper Khafji Shale", is essentially shale with occasional thin reservoir sands. The next unit, the "Upper Khafji Stringers", consists of interbedded sands and shales with minor amounts of ironstone (mainly siderite), and very thin coal layers. Below the stringer sands is the "Main Sand", made up of thick massive sands 200 to 300 feet thick. The lowermost unit, the "Lower Khafji Stringers", is predominantly shale with minor interbedded reservoir sands. The majority of wells drilled to date are vertical and have targeted the "Main Sand" member. As drilling technology has advanced it has now become possible to target additional pay-zones within the "Upper Khafji Stringers" which are best developed on the flanks of the reservoir structure.

A Decision Analytic Approach to Geosteering Operations

“…Although integration of multiple sensors and more-general structural uncertainties are beyond the scope of this case, the Bayesian inference method can be adapted to more-complex geomodels. Indeed, the Bayesian approach is the only consistent way to update probabilities given new information (Bratvold and Begg 2010). This probabilistic view of the reservoir boundaries consistently integrates prior information and real-time data and provides unbiased information for geosteering-decision support.…”

“…Decision analysis applies a sequence of transparent steps to provide clarity of insight into the decision problem (Howard 1988). Bratvold and Begg (2010) presented a method for achieving this clarity, which consists of three main phases (Fig. 4): Structuring/Framing, Modeling/Evaluating, and Assessing/Deciding.…”

“…12 Making geosteering decisions that are logically consistent with the well objectives presumes that the latter have been clearly defined. A geosteering value hierarchy has been developed on the basis of the guidance from Bratvold and Begg (2010) and Parnell et al (2013). The value hierarchy (Fig.…”

“…This requires a learning model on how to use the new data and information to update the old model. A natural choice for such a learning model is Bayes' rule, which provides a consistent "rule" for combining prior information with new information (evidence or likelihood) to generate a posterior (updated) model (Bratvold and Begg 2010).…”

“…The quality of a decision is not a function of the time and resources available(Bratvold and Begg 2010).10 In some situations, real-time data acquired might lead to the re-evaluation of the objectives' relative weight.11 As discussed earlier, most operators use multiple objectives for geosteering decisions. Multiobjective decision analysis is a collection of systematic procedures for evaluating decision alternatives in the face of multiple, conflicting objectives and uncertainties(Keeney and Raïffa 1976).12 In theory, data are received and evaluated continuously, which means that decisions are being made continuously.…”