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Sviridov, Mikhail (Baker Hughes) | Belyaeva, Olga (Salym Petroleum Development) | Podberezhnyy, Maxim (Salym Petroleum Development) | Zverev, Vladimir (Salym Petroleum Development) | Mosin, Anton (Baker Hughes) | Antonov, Yuriy (Baker Hughes)
Summary The West Salym is a Salym Petroleum Development oil field in the Khanty-Mansi region, 120 km southwest of Surgut, Russia. The West Salym oil field was discovered in 1987 and was brought on stream in 2004. The reservoirs vary from fluvial/deltaic to shallow marine deposits. Primary development of the central area of West Salym Field is complete, but the field edges remain undeveloped and potentially attractive. The edges of the field are presented by a mouth bar and characterized by significant structural formation changes, including unknown formation dips and local carbonate concretions and stripes. The sand thickness of the target layer is 15 m, with a minimum oil height of 1 m, which is caused by structural dips and nearby oil/water contact (OWC). These conditions make it difficult to drain the area with geometrically placed wells within the hydrocarbon-saturated layer using well correlation and 3D seismic-interpretation results. Another challenge is the low resistivity contrast between the shale, oil-bearing, and water-bearing layers. This poor contrast complicates the evaluation of reservoir properties and the ability to distinguish different fluid saturations. Two horizontal wells (500 m each) were drilled for the first time in West Salym Field to evaluate capabilities of modern reservoir-navigation technology using deep-azimuthal resistivity technology and advanced data-interpretation software. Drilling of both horizontal wells was improved with a standard wireline logging suite (gamma ray, spontaneous potential, resistivity, density, and neutron) and pressure-testing results available from pilot holes. Logging-while-drilling (LWD) deep-azimuthal resistivity technology has been used in field development, contributing to proactive reservoir navigation. This technology provides input for interpreting an extensive set of multicomponent, multispacing, and multifrequency measurements. These data are usually sufficient to resolve the formation properties in the vicinity of several meters from the wellbore and to adjust the direction of the well trajectory. However, because of time restrictions, very simple resistivity models and only a subset of the data are often used for real-time interpretation. Moreover, the structure of the data subset is often predefined to provide the maximum depth of investigation, neglecting the resolution quality of the formation parameters. In some fields, it can lead to increased uncertainties during reservoir navigation. The data-interpretation software mentioned in this paper has excellent performance and enables real-time processing of the full set of downhole measurements derived from multilayered formation models. This case highlights the first use of this software application in the Russian Federation. The software is dependent on the method of the most-probable parameter combination, and it maintains an optimal balance between the information recovered from the measured data and all available a priori knowledge about the formation structure. The ability to accurately involve a priori information enhances the capability to resolve layers with low resistivity contrasts. Moreover, the inversion software is user-guided, enabling precise monitoring of lateral and vertical changes in the geology. The data-inversion software ensured successful reservoir navigation in the challenging conditions of the West Salym Field. All steering decisions were made according to a consistent and reliable multilayered formation resistivity model that was constructed in real time during drilling. A good net/gross ratio was achieved of approximately 75% for one well and 50% for the other. Post-drilling analysis showed that geometric drilling without reservoir-navigation technology would lower the net/gross ratio to less than 40%.
The Tyumen formation is the main hydrocarbon-saturated layer of the Krasnoleninskoe oil and gas condensate field located in Western Siberia. This formation is characterized by significantly changing structural dips and represented as thin, interbedded shale and sandstone layers. Such a formation structure complicates the real-time evaluation of formation properties, well correlation and proper well placement. This paper presents the results of horizontal well drilling at the Krasnoleninskoe field using advanced resistivity logging technology.
Advanced resistivity logging technology is used in field operations for various applications. This technology includes logging-while-drilling (LWD), a deep-azimuthal resistivity tool, and sophisticated data interpretation software. The tool performs multi-component, multi-spacing and multi-frequency measurements downhole. The measurement set can be configured individually for each particular geology and application type to ensure effective operations. Next, these measurements are transmitted to the surface, where high-performance multi-parametric inversion recovers formation parameters of interest in real-time. The inversion software enables the processing of any combination of tool measurements and is based on a 1D layer-cake model with an arbitrary number of layers to operate with complex multi-layer formations.
Besides the complex laminated structure of the Tyumen formation, an additional challenge is the low resistivity contrast between the shale and sandstone interlayers. This factor is typical for many West-Siberian fields; it complicates the resolution of interlayers and degrades the evaluation accuracy of their parameters.
To overcome these challenges, a set of deep-azimuthal resistivity tool measurements, suitable to resolve thinly laminated formations, was identified and transmitted uphole while drilling. Real-time inversion was performed in a user-controlled mode to ensure the careful tracking of geology changes. These results enabled operational geologists to monitor the formation properties during the drilling.
Data inversion software ensured the accurate evaluation of formation properties and structural dips estimation in complex conditions of the Krasnoleninskoe field. Structural dips recovered by inversion significantly differed from values observed at offset wells, i.e., 5 to 12 degrees, instead of 0 to 2 degrees. A perfect match between the measured and synthetic resistivity data confirmed high confidence of inversion results. Moreover, there was a strong correlation between the structural dip angles estimated from resistivity data and derived from LWD natural gamma-ray (GR) image. Many of shale and sandstone layers observed in the GR curves were resolved by resistivity inversion.
The depth of the remote layer detection was estimated during the job; it enabled geoscientists to delineate the reservoir volume that contributed to the tool measurements.
This case study describes the first application of advanced resistivity logging technology in a complex laminated formation of the Krasnoleninskoe field. This technology enables the resolution of thin interlayers, evaluation of their properties and estimation of structural dips in real time. These parameters are important for proper well placement and accurate petrophysical interpretation. The presented technology is able to increase the efficiency of oil recovery in the complex laminated formations of the Russian West-Siberian fields.
Abstract Drilling operators very often perform reservoir navigation and mapping using extra-deep resistivity tools. Tool responses depend on formation properties tens of meters away from the wellbore and require sophisticated processing by inversion to provide operators with a multilayer resistivity model. The accuracy and reliability of inversion results are very important and need thorough assessment. We present two new methods of inversion quality control, validate their applicability, and provide a comparative analysis with existing methods on several synthetic and field cases. Deterministic and statistical methods of estimation of resistivity, tool detection, and resolution capabilities are applied to evaluate the quality of inversion results. We discuss tool ability to detect single boundary, depth-of-detection (DOD) and depth-of-reliable-detection (DRD) concepts based on covariance matrix analysis, and introduce a new method of DOD estimation based on resistivity model perturbations, with posterior tool response monitoring. We propose a new statistical resolution analysis method related to response-surface technique and compare its results with other approaches. The applicability of the methods considered is validated by guided inversion for typical job stages (pre-well, real-time, post-well) and applications (landing, reservoir navigation, mapping). Inversion results for extra-deep logging-while-drilling (LWD) resistivity tools are usually shown as a multi-layer resistivity distribution map or picture, without a clear indication of the uncertainty of the structures presented on the picture. The uncertainty of inversion results depend not only on tool specifications (i.e., frequency range, electronic noise level and antennae spacings), but on the complexity of surrounding formations as well. The new method for DOD estimation deals with model complexity and gives several estimates based on different subsets of measurements. Common approaches to inversion result quality control only provide partial reliability indicators, usually around the final inverted model. The suggested resolution analysis method generates a statistic from models assessed during inversion execution, analyses it, and eventually provides the resolution accuracy of formation parameters. The method enables identification and quantification of disconnected uncertainty regions, when they exist, thus ensuring an exhaustive analysis of the parameter space. Based on synthetic and field cases considered, we conclude that understanding of uncertainties associated with reservoir navigation requires the application of several data analysis techniques. Complementary use of data inversion, DOD estimation and resolution analysis yield a comprehensive evaluation of the environment and show the realistic capabilities of the tool. The developed methods enabled the implementation of scenario-oriented workflows that deliver not only the final resistivity model but also its reliability indicators. The paper will show how to interpret and evaluate the quality of inversion results provided by vendors. Two new methods to evaluate the result model extend the capability to analyze uncertainty from several different perspectives. Better understanding of the inversion deliverables with the reliability indicators will help the operators to make more confident decisions during reservoir navigation, or posterior oil field development.
Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Russian Oil & Gas Exploration & Production Technical Conference and Exhibition held in Moscow, Russia, 16-18 October 2012. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract In petroleum exploration, reservoir navigation is used for reaching a productive reservoir and placing the borehole optimally inside the reservoir to maximize production. For proper well placement, it is necessary to calculate in real-time parameters of the formation we are drilling in, and the parameters of formations we are approaching. Based on these results, a decision to change the direction of drilling could be made. Modern logging while drilling (LWD) extra-deep and azimuthal resistivity tools acquire multi-component, multi-spacing, and multi-frequency data that provide sufficient information for resolving the surrounding formation parameters. These tools are generally used for reservoir navigation and real-time formation evaluation. However, real-time interpretation software very often is based on simplified resistivity models that can be inadequate and lead to incorrect geosteering decisions. The core of the newly developed software is an inversion algorithm based on a model of transversely-isotropic layered earth with an arbitrary number of layers. The following model parameters are determined in real time: horizontal and vertical resistivities and thickness of each layer, formation dip, and azimuth. The inversion algorithm is based on the method of the most-probable parameter combination. The algorithm has good performance and excellent convergence due to its enhanced capability of avoiding local minima.
Ronald, Andy (BP Exploration Ltd) | Rabinovich, Michael (BP Exploration Ltd) | Ward, Mary (BP Exploration Ltd) | Gordon, Miriam (BP Exploration Ltd) | Bacon, Robert (BP Exploration Ltd) | Tilsley-Baker, Richard (Baker Hughes, a GE company) | Wharton, Paul N. (Baker Hughes, a GE company) | Mosin, Anton (Baker Hughes, a GE company) | Martakov, Sergey (Baker Hughes, a GE company)
The benefits of extra deep azimuthal reading logging-while- drilling (LWD) resistivity tools have been well documented previously in several papers which outlined the advantages of using these types of data to avoid the need for pilot holes and unplanned side-tracks. Typically, the focus of these tools is to land-out the well in a particular target sand and to then maximise net sand length in the well bore.
This paper will demonstrate additional benefits that these types of measurements can offer which include; reducing seismic depth uncertainty whilst increasing the confidence of the reservoir boundaries; and providing more information on the depositional architecture of the reservoir to aid integrated subsurface description. Cost savings can also be realised using these measurements, not only by mitigating pilot holes and unplanned sidetracks, but by increasing the confidence of a geological model during drilling thereby allowing an increased drilling ROP and eliminating costly delays e.g. waiting on interpretation of biostratigraphic data to enable well planning updates to occur.
Finally, this paper will look at the importance of ensuring pre-job modelling is accurate and representative of the types of formations to be drilled, provides alternative scenarios to the reference case model and how case sensitivities can be used to provide models that match the realised outcome, increasing confidence in the results and speeding up the geosteering decision making process.
This work was performed in an offshore Tertiary deepwater turbidite formation, comprising a system of stacked, confined and unconfined sands with complex fill patterns and multiple incision surfaces. The well consisted of 4 individual target sands that dipped to the north and displayed an offset stacking pattern with two sands targeted at the crest and two additional sands down dip. As the downdip target sands were previously unpenetrated, seismic depth uncertainty was large resulting in an opportunity to run extra deep azimuthal resistivity measurements to ensure that the sands could be located and drilled to maximise net sand length in the reservoir section.
High angle wells drilled in turbidite formations can be challenging to geosteer because of the unpredictability of the structure of the formations themselves and because the boundaries between net and non-net intervals are often not distinct due to anisotropic effects. The ability of extra deep directional LWD resistivity tools to remotely detect hydrocarbon bearing reservoir and image the formation boundary when approaching helps to reduce the geological risk. The data from these tools can be quickly and accurately applied to a model which leads to better and more timely decisions that can decrease rig time, reduce costs and increase the probability of drilling a successful well.