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**Industry**

**Oilfield Places**

**Technology**

Schijns, Heather (University of Alberta) | Schmitt, Douglas R. (University of Alberta) | Heikkinen, Pekka (University of Helsinki) | Kukkonen, Ilmo T. (Geological Survey of Finland)

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

Di, Qingyun (Key Laboratory of Engineering Geomechanics, Institute of Geology and Geophysics, Chinese Academy of Sciences) | Li, Diquan (Key Laboratory of Engineering Geomechanics, Institute of Geology and Geophysics, Chinese Academy of Sciences) | Cheng, Hui (Key Laboratory of Engineering Geomechanics, Institute of Geology and Geophysics, Chinese Academy of Sciences) | Fu, Changmin (Key Laboratory of Engineering Geomechanics, Institute of Geology and Geophysics, Chinese Academy of Sciences) | Wang, Miaoyue (Key Laboratory of Engineering Geomechanics, Institute of Geology and Geophysics, Chinese Academy of Sciences)

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

Park, Sunyoung (Seoul National University) | Ha, Wansoo (Seoul National University) | Shin, Changsoo (Seoul National University) | Pyun, Sukjoon (Inha University) | Calandra, Henri (Total)

It is important to find high-velocity structures such as salt domes in exploration seismology because those structures can form traps that confine hydrocarbons. To locate a highvelocity structure, we have to use data that contains information about the structure. In other words, the wavefield we measure must be a function of the depth of the high-velocity structure. However, if the structure is located very deep, it cannot affect the wavefield and cannot be detected. In this context, we consider the detectable depth of a high-velocity structure as the maximum depth of the structure that influences the wavefield we measure near ground level, i.e., that can make the structure be detected. Of course, the penetration depth varies with the change of the shape of the high-velocity structure. But in this study, we set up an acoustic two-layer model and let the second layer represent the high-velocity structure to analyze for general cases. Also, the Laplace-domain 3D modeling algorithm for acoustic media was used. Figure 1 shows the relationship between the amplitude of the Laplace-domain wavefield and the depth of a highvelocity structure when the offset distance is 10 km and the damping constant is 5.

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (0.49)

Takanashi, Mamoru (Center for Wave Phenomena, Geophysics Department, Colorado School of Mines, Japan Oil, Gas and Metals National Corporation) | Tsvankin, Ilya (Center for Wave Phenomena, Geophysics Department, Colorado School of Mines)

Nonhyperbolic moveout analysis plays an increasingly important role in velocity model building because it provides valuable information for anisotropic parameter estimation. However, lateral heterogeneity associated with stratigraphic lenses such as channels and reefs can significantly distort the moveout parameters, even when the structure is relatively simple. Here, we discuss nonhyperbolic moveout inversion for 2D models that include a low-velocity isotropic lens embedded in a VTI (transversely isotropic with a vertical symmetry axis) medium. Synthetic tests demonstrate that a lens can cause substantial, laterally varying errors in the normal-moveout velocity (Vnmo) and the anellipticity parameter h. The area influenced by the lens can be identified using the residual moveout after the nonhyperbolic moveout correction and the dependence of errors in Vnmo and h on spreadlength. To remove lens-induced traveltime distortions from prestack data, we propose an algorithm that involves estimation of the incidence angle of the ray passing through the lens for each recorded trace. Using the velocity-independent layer-stripping method of Dewangan and Tsvankin, we compute the lensinduced traveltime shift from the zero-offset time distortion (i.e., from “pull-up” or “push-down” anomalies). Synthetic tests demonstrate that this algorithm substantially reduces the errors in the effective and interval parameters Vnmo and h. The corrected traces and reconstructed “background” values of Vnmo and h are suitable for anisotropic time imaging and producing a high-quality stack.

Nonhyperbolic moveout analysis is performed under the assumption that the overburden is laterally homogeneous on the scale of spreadlength. However, even gentle structures often contain velocity lenses, whose width is smaller than the spreadlength (Armstrong et al., 2001; Fujimoto et al., 2007; Takanashi et al., 2008; Jenner, 2009). For isotropic media, lateral heterogeneity of this type has been recognized as one of the sources of the difference between the moveout and true medium velocities (Al-Chalabi, 1979; Lynn and Claerbout, 1982; Toldi, 1989; Blias, 2009). The anellipticity parameter h, responsible for nonhyperbolic moveout in VTI media, is sensitive to correlated traveltime errors (Grechka and Tsvankin, 1998). Still, overburden heterogeneity is seldom taken into account in nonhyperbolic moveout inversion. In principle, laterally varying anisotropy parameters can be estimated from anisotropic reflection tomography (e.g. Woodward et al., 2008). However, if the lens location is unknown, its contribution to traveltimes can hinder accurate Here, we study the influence of velocity lenses on nonhyperbolic moveout inversion for 2D VTI models and propose a correction algorithm designed for gently dipping anisotropic layers.

To analyze lens-induced distortions, we perform 2D finite difference simulations for a model that includes a low-velocity isotropic lens inside a VTI layer (Figure 1). The lens creates a maximum time distortion (or push-down anomaly) of 18 ms. Trim statics Trim statics involves cross-correlation between a near-offset trace and all offset traces, which helps evaluate the statics shifts needed to eliminate the residual moveout and make all traces kinematically equivalent to the zero-offset trace. Thus, trim statics increases stack power and generates a stack that kinematically reproduces the zero-offset section.

Oilfield Places: Oceania > Australia > Western Australia > North West Shelf > Browse Basin > Ichthys Gas Field (0.99)

Tsuji, Takeshi (Kyoto University) | Nakata, Norimitsu (Kyoto University) | Matsuoka, Toshifumi (Kyoto University) | Dvorkin, Jack (Stanford University) | Nakanishi, Ayako (JAMSTEC) | Kodaira, Shuichi (JAMSTEC)

Chou, T. George (Chevron Energy Technology company) | Sydora, Larry (Chevron Energy Technology company) | Hicks, Doug (Chevron Nigeria Limited) | Iyiola, Sunkanmi (Chevron Nigeria Limited) | Nworah, Nche (Chevron Nigeria Limited) | Arowolo, Isaac (Chevron Nigeria Limited)

Frequency Bandwidth – Improve maximum usable frequency through acquisition and processing,

Signal-to-Noise Ratio – Reduce random and coherent noise through acquisition and processing,

De-multiple – Suppression of long and short period multiples without degrading primary energy,

Repeatability – Source and receiver positions for monitor survey,

Converted Wave – Acquisition of high quality converted PS-wave data,

Operational Doability – Ease with which operation can be conducted over the producing field,

Cost – Cost over the life of the field,

System Reliability – Sustainability of acquisition system hardware over the life of the field.

The survey was conducted using a typical land acquisition style with three (3) phased operations of roll-in, roll-along and roll-off.

OBN acquisition completed ahead of schedule in a safe and efficient manner.

Acquisition around the surface facilities (e.g. FPSO, SPM, Tankers, Rig etc) ran smoothly with productivity above expected project average.

acquisition, acquisition style, Agbami Field, artificial lift system, bandwidth, data, data quality, development, field, formation evaluation, gas injection method, gas lift, Nigeria, node, OBN, operation, production control, production monitoring, reference, reservoir, Reservoir Management, surveillance, survey, technology

Oilfield Places:

- Africa > Nigeria > Nigeria Offshore > Niger Delta > Agbami Oil Field (0.99)
- North America > United States > Alabama > Star Gas Field (0.98)

Sunday, Amoyedo Sunday (ConocoPhillips School of Geology & Geophysics, University of Oklahoma) | Slatt, Roger (ConocoPhillips School of Geology & Geophysics, University of Oklahoma) | Marfurt, Kurt (ConocoPhillips School of Geology & Geophysics, University of Oklahoma)

change, Charlie, Charlie sandstone, effect, flow assurance, Fluid Dynamics, formation evaluation, forties field, implication, overburden, pressure, production control, production monitoring, reservoir geomechanics, reservoir strain, sand production, strain, stress, survey, time, time lapse, well logging, wellbore integrity

Oilfield Places:

- Europe > United Kingdom > North Sea > Central North Sea > Forties Oil Field > Forties Formation (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Forties Formation (0.99)

SPE Disciplines:

- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Facilities Design, Construction and Operation > Flow Assurance > Solids (scale, sand, etc.) (0.89)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Integration of geomechanics in models (0.88)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (0.71)