Tuesday, July 30, 2019

Mapping Porosity in Malaysia

Once thought to be useful primarily in carbonate reservoirs because of a more recognizable porosity-acoustic impedance relationship, inversion for porosity mapping has also proven powerful in sand reservoirs. PETRONAS Carigali, the upstream operating arm of the Malaysian national oil company, has used seismic inversion to optimize drilling locations in the Dulang West field in the Malay basin of the South China Sea.

The Dulang field has an estimated 850 million barrrels original oil in place (OOIP). In the first stage of development, more than 100 wells were drilled in the central area of the faulted anticlinal structure, producing from an oil and gas column of up to 150 m [492 ft] of stacked sandstones. The next stage of development focuses on the Dulang West portion, in which plans call for 25 wells from a 32-slot platform.

The four delineation wells indicate a reservoir too complex to understand from well data alone.The main reservoirs are fine-grained, discontinuous sands interbedded with shales and coals. The sand bodies are preferentially oriented, suggesting permeability anisotropy on the scale of the field. Porosity, permeability and their relationship to each other show great variability - for example, permeability can vary from 50 to several hundred millidarcies for a median porosity of 25%. In the central area developed earlier, close well spacing permitted property mapping from logs. But in Dulang West, engineers have relied on inversion of the 3D seismic data to extend information contained in the delineation wells to map porosity across the field.

After the poststack seismic and log data were tied at the right depths and inverted for acoustic impedance, log properties were tested for their correlation with the AI values at the respective well locations using the Log-Property Mapping module of the RM Reservoir Modeling software. Only porosity was found to correlate significantly with acoustic impedance, with a trend similar to that of the chalks of the East Hod field. Extending the log porosity values away from the four wells using the seismic inversion results as a guide produced a reservoir porosity map.


An integrated assessment of porosity and structure allowed interpreters to propose drilling locations. Areas of higher porosity in the south were deemed more promising than lower-porosity areas in fault block to the north. The well prognosis module of the RM system allowed several potential sites to be quickly investigated for reservoir quality and likely reserves.

The reservoir model built from the seismic data included not only the traditional aspect of reservoir structure, but also the total volume of porosity in each volume element of the seismic cube. This model was scaled up for input to a fluid-flow simulator. Permeability was distributed throughout the model by applying a porosity-permeability transform to the seismically guided porosity map. The new model provided a better estimation of production over a simulated seven-year period than that obtained by other methods.

In addition, areas of high acoustic impedance were interpreted to be shaly or to have poor reservoir development, enabling better placement of planned wells. Recent appraisal drilling southeast of well 6G-1.3 , testing oil potential downdip of gas inferred from an especially low AI anomaly, encountered 18 m [59 ft] of good quality, 18% porosity gross sand. Althought the sand was wet, agreement with the model was good, with 18.8 m [62 ft] and 19% porosity predicted. Two development wells, D1 and D2, further demonstrate the predictive power of the method. 


In some environments, seismic reflection amplitude variation with offset (AVO) can be used as a reservoir management tool to indicate hydrocarbon extent. The AVO technique relies on the observation - backed up by physics- that pore fluid imprints a signature on the amplitude of a seismic reflection. To see this signature, seismic data must be viewed at different angles of reflection. Depending on the type of pore fluid in the juxtaposed rock layers, the amplitude of the reflection may increase, decrease , or remain constant as the  as the reflection angle at the boundary increases. The incident angle of the seismic wave can be expressed in terms of offset, or distance , between seismic source and receiver - a congruent quantity more easily measured than an angle at some depth.

A common way to use AVO to characterize reservoirs is to identify a hydrocarbon AVO signature- for example, the AVO response of a gas reservoir- and comb the 3D seismic volume for other areas with similar signatures. This can result in discoveries of bypassed hydrocarbon as well as extension or delineation of existing reservoirs. The practice assumes that lithology does not have enough lateral variation to affect the seismic amplitudes, so that all AVO effects are due to changes in pore fluid type. The seismic data must be processed to preserve relative amplitudes, and also must be analyzed before stacking. 

Some lithologies show less obvious AVO sensitivity to pore fluid change than others. Carbonates and low-porosity sandstones tend to have less evident AVO signatures than high-porosity sandstones, and special care must be taken in applying the technology in these areas.

In an example from the mature BK field in the Gulf of Mexico, the successful incorporation of AVO analysis helped Oryx Energy Company engineers identify extensions of the reservoir that might have gone undrilled. The quality of the AVO results convinced management to free up money for drilling that had been allocated elsewhere.

The BK field lies off the flank of a shallow salt and shale diaper in 5 m of water near the Lousiana Gulf Coast. The reservoir, discovered in the late 1940s, has produced 300 billion cubic feet (Bcf) of gas. The map of the 5000-m [16,400-ft] deep structure had ben constructed primarily with well control, and the new 78-km2 survey, designed to provide incremental structural and stratigraphic information, changed the structural map significantly.

AVO analysis was introduced to better delineate the gas reservoir and reduce risk in choosing drilling locations. The analysis required a seismic cube for two different families of offsets. Data processing followed the same sequence as for the full 3D cube, except the data were separated into a near offset volume with offset ranges from zero to 3800 m and a far offset volume with offset from 3800 to 5800 m. 

Forward modeling using logs from producing wells indicated the gas zones have an AVO signature of amplitude increasing with offset. Interpretation consisted of finding other areas in which the near-offset volume has low amplitudes and the far-offset volume has higher amplitudes. 

The technique is demonstrated on a pair of seismic lines exctracted from the 3D volume. The AVO signature on Line 1215 at the gas-producing well BK-15 is the standard to which Line 1235 is compared to determine the likelihood of hitting gas at the proposed location BK-16. A color-coding system was devised to discriminate increasing AVO trends from decreasing ones. Results of the analysis show the BK-16 location to be similar to, and perhaps even more promising than, the producer BK-15. 

Initial production from the BK-16 well was 15.4 MMcf/D and 210 barrels of condensate per day from 25 m [82 ft] of 20% porosity sand. Sand quality is better than that found in the BK-15 well, refuting speculation that sand quality degrades to the northwest. And following the BK-16 well, two additional successful wells have been drilled within the region of AVO gas signature.

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