The Unconventional Shale Reservoirs of Jafurah Basin: An Integrated Petrophysical Evaluation Using Cores and Advanced Well Logs

2017 ◽  
Author(s):  
Ghadeer Al-Sulami ◽  
Mohammed Boudjatit ◽  
Mohammed Al-Duhailan ◽  
Salvatore Di Simone
Keyword(s):  
Well Logs ◽  
Shale Reservoirs ◽  
Petrophysical Evaluation

Petrophysical Type Curves for Identifying the Electrical Character of Petroleum Reservoirs

2007 ◽  
Vol 10 (06) ◽  
pp. 711-729 ◽  
Author(s):  
Paul Francis Worthington
Keyword(s):  
Water Saturation ◽  
Early Stage ◽  
Well Logs ◽  
Log Analysis ◽  
Well Log ◽  
Formation Water ◽  
Water Conductivity ◽  
Core Data ◽  
Water Saturated ◽  
Petrophysical Evaluation

Summary A user-friendly type chart has been constructed as an aid to the evaluation of water saturation from well logs. It provides a basis for the inter-reservoir comparison of electrical character in terms of adherence to, or departures from, Archie conditions in the presence of significant shaliness and/or low formation-water salinity. Therefore, it constitutes an analog facility. The deliverables include reservoir classification to guide well-log analysis, a protocol for optimizing the acquisition of special core data in support of log analysis, and reservoir characterization in terms of an (analog) porosity exponent and saturation exponent. The type chart describes a continuum of electrical behavior for both water and hydrocarbon zones. This is important because some reservoir rocks can conform to Archie conditions in the fully water-saturated state, but show pronounced departures from Archie conditions in the partially water-saturated state. In this respect, the chart is an extension of earlier approaches that were restricted to the water zone. This extension is achieved by adopting a generalized geometric factor—the ratio of water conductivity to formation conductivity—regardless of the degree of hydrocarbon saturation. The type chart relates a normalized form of this geometric factor to formation-water conductivity, a "shale" conductivity term, and (irreducible) water saturation. The chart has been validated using core data from comprehensively studied reservoirs. A workflow details the application of the type chart to core and/or log data. The analog role of the chart is illustrated for reservoir units that show different levels of non-Archie effects. The application of the method should take rock types, scale effects, the degree of core sampling, and net reservoir criteria into account. The principal benefit is a reduced uncertainty in the choice of a procedure for the petrophysical evaluation of water saturation, especially at an early stage in the appraisal/development process, when adequate characterizing data may not be available. Introduction One of the ever-present problems in petrophysics is how to carry out a meaningful evaluation of well logs in situations where characterizing information from quality-assured core analysis is either unavailable or is insufficient to satisfactorily support the log interpretation. This problem is especially pertinent at an early stage in the life of a field, when reservoir data are relatively sparse. Data shortfalls could be mitigated if there was a means of identifying petrophysical analogs of reservoir character, so that the broader experience of the hydrocarbon industry could be utilized in constructing reservoir models and thence be brought to bear on current appraisal and development decisions. Here, a principal requirement calls for type charts of petrophysical character, on which data from different reservoirs can be plotted and compared, as a basis for aligning approaches to future data acquisition and interpretation. This need manifests itself strongly in the petrophysical evaluation of water saturation, a process that traditionally uses the electrical properties of a reservoir rock to deliver key building blocks for an integrated reservoir model. The solution to this problem calls for an analog facility through which the electrical character of a subject reservoir can be compared with others that have been more comprehensively studied. In this way, the degree of confidence in log-derived water saturation might be reinforced. At the limit, the log analyst needs a reference basis for recourse to capillary pressure data in cases where the well-log evaluation of water saturation turns out to be prohibitively uncertain.

Maximizing Information through Data Driven Analytics in Petrophysical Evaluation of Well Logs

2015 ◽  
Author(s):  
Vikas Jain ◽  
Kais Gzara ◽  
Gennady Makarychev ◽  
Chanh Cao Minh ◽  
Denis Heliot
Keyword(s):  
Well Logs ◽  
Data Driven ◽  
Petrophysical Evaluation

Permeability evaluation in a glauconite‐rich formation in the Carnarvon Basin, Western Australia

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Yujin Zhang ◽  
Henry A. Salisch ◽  
Christoph Arns
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Well Logs ◽  
Permeability Prediction ◽  
Geophysical Logs ◽  
Conventional Logs ◽  
Complex Formations ◽  
Permeability Evaluation ◽  
Petrophysical Evaluation ◽  
Carnarvon Basin

It is usually difficult for petroleum engineers and geoscientists to obtain reliable estimates of permeability from geophysical logs, especially in lithologically complex formations such as the Mardie Greensand Formation in the Carnarvon Basin, Australia, which consists of lower Cretaceous glauconite‐rich sandstones. This paper presents an alternative petrophysical evaluation of permeability in this formation through the integration of the geological and petrophysical analyses. Neural network techniques were used to establish permeability prediction models in cored wells or sections and to predict permeability from well logs in uncored wells or sections. The permeabilities obtained from minipermeameter measurements were taken as the basis and reference for the petrophysical evaluation. Four log‐derived parameters, which best reflect the permeability in the Mardie Formation, were defined and extracted from the available conventional logs. These parameters (not original log responses) were taken as the log inputs to evaluate permeability. Through the training, testing, and validation of the networks using the log and core data in the cored intervals, a permeability prediction model/network was established. Further, the permeabilities in 15 wildcat wells were determined from conventional well logs. The results indicate that the petrophysical evaluation of permeability is valid and applicable in the Mardie Formation.

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