Shallow Gas Cloud Research Articles

Direct shear-wave seismic survey in Sanhu area, Qaidam Basin, west China

The formation containing shallow gas clouds poses a major challenge for conventional P-wave seismic surveys in the Sanhu area, Qaidam Basin, west China, as it dramatically attenuates seismic P-waves, resulting in high uncertainty in the subsurface structure and complexity in reservoir characterization. To address this issue, we proposed a workflow of direct shear-wave seismic (S-S) surveys. This is because the shear wave is not significantly affected by the pore fluid. Our workflow includes acquisition, processing, and interpretation in calibration with conventional P-wave seismic data to obtain improved subsurface structure images and reservoir characterization. To procure a good S-wave seismic image, several key techniques were applied: (1) a newly developed S-wave vibrator, one of the most powerful such vibrators in the world, was used to send a strong S-wave into the subsurface; (2) the acquired 9C S-S data sets initially were rotated into SH-SH and SV-SV components and subsequently were rotated into fast and slow S-wave components; and (3) a surface-wave inversion technique was applied to obtain the near-surface shear-wave velocity, used for static correction. As expected, the S-wave data were not affected by the gas clouds. This allowed us to map the subsurface structures with stronger confidence than with the P-wave data. Such S-wave data materialize into similar frequency spectra as P-wave data with a better signal-to-noise ratio. Seismic attributes were also applied to the S-wave data sets. This resulted in clearly visible geologic features that were invisible in the P-wave data.

Optimizing Acquisition Geometry in Shallow Gas Cloud Using Particle Swarm Optimization Approach

Many hydrocarbon explorations in mature fields have been severely affected by complex and overburdening issues, such as shallow gas accumulation, gas pockets, and gas seepage. In this work, a new forward modelling technique is proposed in evaluating the potential survey design for fields affected by shallow gas cloud. In recent years, the implementation of innovative acquisition layouts has been producing significantly better seismic images, especially in the low illumination subsurface area. However, the uncertainty of the effectiveness in new acquisition design subsurface coverage always become a major stumbling block. To overcome this constraint, an optimization approach is suggested through the smart source and receiver location arrangement on the surface, with significant alignment to the conventional source and receiver arrangement approach. The particle swarm optimization (PSO) method is used to find the source-receiver configuration with maximum subsurface illumination coverage for the gas affected field situated in Malaysia Basin. Implementation of the PSO algorithm requires both a velocity model building process and wave field extrapolation from a target reflector to the surface level. The wave field data then was used to simulate receiver optimization outputs which eventually determined the subsurface illumination coverage. The results from the new optimization method for both synthetic model and Malaysia Basin data, offer a greater understanding of the consequences of obstacles caused by shallow anomalies with respect to seismic acquisition, data processing, and interpretation.

Extracting geologic information directly from high-resolution full-waveform inversion velocity models — A case study from offshore Trinidad

The East Coast Marine Area (ECMA) of Trinidad and Tobago contains producing gas fields where the imaging of seismic data is known to be challenging. This difficulty has been attributed to the combination of the Dolphin Main Fault, with more than 1 km of throw and large velocity contrasts of up to 30% in magnitude across it, and shallow gas and gas clouds causing very high attenuation. These factors lead to difficulties producing reliable and consistent velocity models. Previous velocity models — generated using traveltime tomography — contained inaccuracies that led to poor imaging and structural positioning, resulting in uncertainty when planning exploration and development drilling programs. In an attempt to reduce these uncertainties, a full-waveform inversion (FWI) feasibility study was performed over the most problematic area, with an initial velocity model built from a combination of legacy prestack time and depth migration velocity models and additional first-break refraction tomography. The geologic complexity near the main fault and the associated poor seismic data quality meant this model gave a poor fit between the synthetic and observed data (from a cycle-skipping point of view) at the lowest usable frequency. This led to the idea of applying a diving-wave-driven, offset-stripping workflow across each frequency band in the FWI, going from 3.5 Hz to 7.5 Hz. After successful application on the test area, the workflow was applied to ∼1400 km2 of 3D seismic over the ECMA. The final velocity model is structurally consistent and highly resolved, containing detailed shallow geologic features such as mud volcanoes, well-defined faults, and potential gas anomalies that were not visible on the legacy tomographic model. A blind test of well-pressure data correlates strongly with velocity drops in the FWI model, showing that FWI models can potentially provide very good input to regional pore-pressure-prediction studies.

Quantifying the uncertainty of Gross Rock Volume: a decade of time-to-depth conversion in Sepat Field, Malay Basin

Gross Rock Volume (GRV) range and uncertainty estimation from depth maps is important for resource assessment, and represents a significant contribution from seismic interpretation into the reservoir model. Subsurface uncertainty comes from different factors such as errors in time and depth maps, number of wells drilled, property and facies modelling. This paper focuses on the sensitivity of GRV to various velocity models as the implementation of seismic technologies changed from 2002 to 2013 and as conventional time-to-depth migrated multi-component data was used for depth conversion. GRV estimates from different depth maps are captured and utilized for volumetric and structural uncertainty analysis. Sepat Field was discovered in 1983 and has been interpreted structurally as a 30 km long by 10 km wide, E-W trending, four-way dip closure dissected by normal faults. Like many of the oil and gas fields in the Malay Basin, it is significantly affected by shallow gas clouds especially in the crestal area of the structure (Figure 1). Shallow gas clouds cause amplitude and frequency attenuation and time structure sagging effects which lead to significant uncertainties in structural and stratigraphic mapping of reservoirs below the shallow gas area, and subsequently in the hydrocarbon resource assessment of these fields (Ghazali, 2013). A decade of various seismic vintages and studies are applied to the field in order to achieve better and more accurate depth predictions and quantify uncertainty. As a solution to the shallow gas cloud issue, a 4C seismic survey was acquired in 2012 with the objective of recording both compressional and mode converted shear wave (PS). Acquisition and Processing of PS mode conversions enables improvement in subsurface imaging and subsequent reservoir characterization (Barkved et al., 2004).

Seismic Data Analysis to the Converted Wave Acquisition: A Case Study in Offshore Malaysia

Many fields in offshore Malaysia suffer from the presence of shallow gas cloud which is one of the major issues in the basin. Seismic images underneath the gas cloud often show poor resolution which makes the geophysical and geological interpretation difficult. This effect can be noticed from the amplitude dimming, loss of high-frequency energy, and phase distortion. In this work, the subsurface will be analyzed through the geophysical interpretation of the converted P-S data. This P-S converted dataset was obtained through ocean bottom cable (OBC) procedure which was conducted at a shallow gas affected field located in Malaysian Basin. The geophysical interpretation process begin by picking the clear faults system and horizons, followed by thorough post-stack seismic data processing procedure. Finally, the attributes analyses were implemented to the seismic section in order to image the unseen faults system. The interpreted seismic sections show significant improvement in the seismic images, particularly through median filter process. Moreover, the combination of structural smoothing and variance procedure had contributed to the correct faults location interpretation.

Shallow gas cloud illumination analysis by the focal beam method

This research will address the illumination issue of seismic data below a shallow gas cloud, also known as shallow gas accumulation. In general, poor and distorted seismic data underneath gas zones depend on four major factors; namely the velocity of the gas zones, the depth of the target reflector, the location of the source and the receiver during seismic acquisition, and the frequency of the seismic signals. These factors will be scrutinized in detail by using the focal beam method. The focal beam method incorporates the double focusing concept in order to obtain two important attributes for illumination analysis: (i) Resolution function beam, (ii) amplitude versus ray parameter (AVP) imprint, which is obtained by transforming the modelled data into the radon domain. Both illumination attributes are then applied to a gas-affected field in the Malaysia Basin. The results show well-defined illumination beneath the shallow anomalies and provide a better representation of the subsurface. © 2016 Sinopec Geophysical Research Institute.

The application of data conditioning, frequency decomposition and RGB colour blending in the Gohta discovery (Barents Sea, Norway)

Geological Expression workflows, involving data conditioning and frequency decomposition can be used to detect subtle changes within the seismic signal, increase the confidence on the seismic interpretation and de-risk exploration and appraisal wells. This paper looks at the application of these workflows to the Permian carbonates in the Gohta discovery (Barents Sea, Norway) and how the results can help to increase the confidence on the proposed appraisal programme. As a preparation for the rest of the workflow, the data was conditioned using post imaging techniques. The first step involved noise cancellation of the seismic data using structurally oriented and edge-preserving algorithms. An area of poor quality data due to shallow gas clouds was identified to the south of the Gohta structure. In this area, a stronger noise attenuation workflow followed by an amplitude normalisation was applied to increase the reflector continuity. Both noise cancellations were then combined and this noise cancelled dataset was used as an input for the spectral enhancement. Two different spectral enhancements were tested using different methods; one involved the enhancement of the low frequencies using a low-pass high-cut filter, and the other one involved an enhancement of both the low and the high frequencies, aiming for a white spectrum. Frequency decomposition and RGB blending were applied on both enhanced datasets, using two different methods: one involving a short window-based Fast Fourier Transform, and the other one involving an adaptive matching pursuit algorithm. The bright colours observed in the blends were interpreted as an indicator of the presence of oil and gas, while colour changes were interpreted as changes in reservoir thickness, lithology or fluid content. The results of this work supported the presence hydrocarbons on the proposed location of the Gohta appraisal well (7120/1- 4 S), which was drilled in 2014 and encountered gas but the testing in the oil zone was inconclusive because of the technical problem of isolating gas flow from the oil zone, proving the validity of this technique as a DHI.

Acoustic 2D full waveform inversion to solve gas cloud challenges

<p>The existing conventional inversion algorithm does not provide satisfactory results due to the complexity of propagated wavefield though the gas cloud. Acoustic full waveform inversion has been developed and applied to a realistic synthetic offshore shallow gas cloud feature with Student-t approach, with and without simultaneous sources encoding. As a modeling operator, we implemented the grid based finite-difference method in frequency domain using second order elastic wave equation. Jacobin operator and its adjoint provide a necessary platform for solving full waveform inversion problem in a reduced Hessian matrix. We invert gas cloud model in 5 frequency band selected from 1 to 12 Hz, each band contains 3 frequencies. The inversion results are highly sensitive to the misfit. The model allows better convergence and recovery of amplitude losses. This approach gives better resolution then the existing least-squares approach. In this paper, we implement the full waveform inversion for low frequency model with minimum number of iteration providing a better resolution of inversion results.</p>

Recognizing pitfalls of seismic structure and amplitude anomalies in Osprey field, Brunei

The Osprey gas field was discovered in 1975 in the western offshore area of Brunei Darussalam. Two discovery wells penetrate the hanging wall of two separate growth faults and are associated with bright seismic amplitudes. Multiple thin reservoirs are separated by shales of 10 to a few hundred meters in thickness. In addition to seismic tuning of thin layers, there are many shallow gas clouds above these reservoirs, which cause significant and varying amount of push-down in seismic time data. Visualizing as seismic depth data reduces the amount of push-down but doesn’t remove it totally because, to date, the velocity model has been neither detailed nor accurate enough to fully constrain the seismic processing. Time-to-depth conversion includes significant uncertainties in the reservoir time interpretation, with only one well control per fault block. The shallow gas clouds also cause severe amplitude distortion at reservoir levels in the time and depth data, resulting in difficulties for discriminating gas distribution from stratigraphic variations or tuning effects. Furthermore, the shallow gas clouds cause false or enhanced rollover structures and artificial fault features adjacent to expressions of “real” features in the seismic data. Thus, estimates of reservoir spatial distribution and hydrocarbon volumes have large uncertainties. Recognizing these structure and amplitude pitfalls and handling them properly are important to improve reservoir understanding and volumetric estimations and to optimize development of the field. We have uncovered a variety of pitfalls and developed some mitigation methods. One method uses the seismic flat spot to correct the gas push-down effect, and the check-shot velocity was adjusted accordingly. This led to reduced uncertainty in the reservoir depth prognosis of the planned wells. Four wells were drilled in 2014, and the actual depth in all wells came out within only a 4-m difference, validating the correction method for shallow gas push-downs.

Structural Enhancement in Shallow Gas Cloud Region

This research will address the issue of poor structural interpretation below complex overburden and shallow anomaly that cause wave field distortion. The main objective of this research paper is to present the result of seismic interpretation over a seismic line extracted from a shallow gas filed located in Malay Basin. The readers will be briefly explained on the seismic data properties of shallow gas cloud, followed by methodology and techniques used in interpreting the data. Interpretation techniques used in this research work include the seismic data analysis based on the seismic attributes. The outcome from this work aims at recovering the hidden structure that cannot be seen in the data after processing and imaging sequences.

Seismic Illumination Analysis in Poor Oil & Gas Field Data by Using Focal Beam Method

The area underneath shallow gas cloud is an area where the image of subsurface data is generally poor. This distorted image underneath gas zones usually contains precious information of hydrocarbon accumulation. Previously, we analyse the factors contribute to poor subsurface seismic image underneath the gas cloud model and use focal beam technique to understand subsurface illumination information. Encourage by model-based success, we shift our focus to data-based application by applying the focal beam technique into a real field data. The results from this field were analyse in term of resolution function and amplitude versus ray parameter (AVP) imprint for different reflector depth, followed by acquisition analysis on the surface level. For this purpose, a velocity data of a field located in Malay Basin was built before applying the focal beam calculation. We will demonstrate that by using focal beam analysis for this field, we will able to obtain good imaging particularly for target reflector at 2000ms, 4000ms and 6000ms depth, provided the full 3D acquisition geometry was used during focal beam application.

Recent advances in multicomponent processing

The evolution of 3-D multicomponent processing and collection methods has increased our information about reservoirs. Processing techniques now exist to generate a time or depth image of P-to-S converted waves (or C-waves) using ocean‐bottom sensors. These images can enhance reservoir characterization, especially when shallow gas clouds may inhibit compressional wave propagation.