July-August 2000
Volume 1 No. 4
Early Results of Through Casing Resistivity Field Tests
H. M. Maurer and J. Hunziker
ABSTRACT
Measuring formation resistivity behind metal casing allows the application of
well-established water saturation evaluation methods to a producing reservoir.
This new technology can be employed in several applications, especially in low
porosity settings where water saturation estimates based on pulsed neutron
readings are problematic. However, building an instrument capable of measuring
formation resistivity through metal casing constitutes several major technical
and scientific challenges.
In cooperation with a consortium of oil companies and the Gas Research
Institute, Baker Atlas has developed a through casing resistivity tool. The
instrument has completed several successful tests under field conditions.
Recordings of through-casing formation resistivity agree closely with open hole
logs. Compensation for casing imperfections and collars is apparently
successful.
Applications of Resistivity Modeling in Reservoir Development: Examples from Balder Field, Norwegian North Sea
F. M. Haynes, D. Bergslien, O. M. Burtz, and M. S. Munkholm
ABSTRACT
The massive Paleocene oil sands of the Balder Field are overlain by several
thinly bedded Eocene sand-prone packages of variable facies and reservoir
quality. Although these sands have been penetrated by numerous exploration and
development wells, uncertainty remains as to their extent, distribution, and
ultimate effect on reservoir performance. The section is geologically complex
(thin beds, injected sands, shale clasts and laminae, and faulting), and also
contains a field-wide primary gas cap. With a depletion plan involving both gas
and water injection, geologic/reservoir characterization of the Eocene is
critical for prudent resource management during depletion. With this goal,
resistivity modeling and core-based thin bed reservoir description from the
first phase of development drilling have been integrated with seismic attribute
mapping.
Detailed core description, core permeability and grain size distribution data
delineate six facies and help in distinguishing laterally continuous massive
and laminated sands from potentially non-connected injection sands and
non-reservoir quality siltstones and tuffs. Volumetric assessment of the
thin sand resource has been enhanced by 1-D forward modeling of induction log
response using a commercial resistivity modeling program, RtBAN. After defining
beds and facies with core and high resolution log data, the AHF60 array induction
curve response was approximated using the 6FF40 response. Because many of the
beds were thinner than 6FF40 resolution, the modeling is considered to provide
a lower bound on Rt. However, for most beds this model-based Rt is
significantly higher than that provided by one-foot vertical resolution shallow
resistivity data, and is thought to be the best available estimate of true
formation resistivity. Sensitivities in STOOIP were assessed with multiple Rt
earth models which can later be tested against production results. In addition,
water saturation height functions, developed in vertical wells and thick beds,
can be validated in deviated wells with thin beds.
Sand thickness models constrained by this log- and core-based petrophysical
analysis were used to build impedance seismic synthetic sections from which
seismic attributes could be extracted and calibrated. The model-based attribute
calibration was then applied to the seismic impedance 3-D cube permitting sand
thickness to be mapped and reservoir geology to be modeled with significantly
more detail than previously possible. These results will guide the field’s
reservoir management and assist in the delineation of new targets.
Using the Epicentre Data Model to Preserve the Value of Well Log Data
Cary Purdy and Mark Vining
ABSTRACT
Although technical data, such as well log curves, are an important asset of petroleum industry exploration and production companies, frequently they are not organized or cataloged efficiently. Instead, data typically have been placed in corporate data files or left under the control of individual application programs. Improved sensor and acquisition technology have resulted in increased data volumes as well as increased complexity of data structures. Data modeling defines a common way to store, retrieve, and exchange data consistently, improving efficiency and reducing the cost of processing it. A data model gives context and definition to its entities, and defines relationships among them. Purchased well log data can lose significant value, because the cost of understanding and reformatting it for storage is often prohibitive. For applications to effectively exchange information, they require a common or shared data model. The Epicentre data model addresses the issues of data storage, retrieval, and organization of oil industry exploration and production data. Epicentre contains the names and definitions for more than 820 real world, technical, and business entities concerned with the petroleum industry. It is an object-oriented model that utilizes multiple inheritance. Information is retrieved from the database by Standard Query Language queries. The logical structure is represented using Universal Modeling Language. We describe the entities needed to understand log data. The well log entity is analyzed at the property level as an example. We illustrate schematically the database loading sequence for a typical gamma-ray log.