Seismic reservoir characterization of gas-sand deposits in the Kutei basin, Indonesia

Kutei Basin has the second largest hydrocarbon reserve in Indonesia. In addition to the Miocene inversion related structural traps, slope-fan and channel stratigraphic traps are also important traps in this basin. To guide stratigraphic traps explorations in the basin, the seismic stratigraphy, attributes, and AI inversion methods are integrated to identify and map the reservoir seismic facies, porosity, and pore-fluid. Well data indicates that the studied reservoirs are filled by gas. Seismic data shows that there are two main gas-sand reservoirs corresponding to strong amplitude anomaly. Seismic stratigraphy analysis, guided by seismic attributes, shows that these gas-sand reservoirs were deposited in the channel and local fan facies. The AI inversion is applied to identify and map the porosity and pore-fluid of these two sand reservoirs. Future well locations are identified by integrating the facies, porosity, and pore-fluid maps.

Time-lapse detection using raypath interferometry

ABSTRACTThe objective of most seismic time-lapse studies is to detect rock property changes in a subsurface formation caused by fluid withdrawal or injection, often by comparing seismic reflection images of the subsurface before and after the operation. Since rock property changes can affect the amplitudes of seismic reflection events associated with the boundaries of the formation, amplitude anomalies are the usual target of time-lapse experiments. Sometimes, however, particularly in harder, less porous rocks, a seismic amplitude anomaly can be relatively small and difficult to detect. There is a secondary time-lapse effect, however, which may be detectable even in the absence of a significant reflectivity anomaly: the time-delay of reflections from layers beneath a formation whose wave propagation velocity has been altered by pore fluid change. We introduce a near-surface correction technique for land data, which we call joint raypath interferometry, to specifically enhance and detect small time delays between corresponding events on two or more comparable time-lapse seismic images. We demonstrate the technique first on a numerical model, then on an actual time-lapse field survey in which a reflection amplitude anomaly is difficult to detect.

AVO analysis aids in differentiation between false and true amplitude responses: a case study of El Mansoura field, onshore Nile Delta, Egypt

The seismic amplitude versus offset (AVO) analysis has become a prominent in the direct hydrocarbon indicator in last decade, aimed to characterizing the fluid content or the lithology of a possible reservoir and reducing the exploration drilling risk. Our research discusses the impact of studying common depth point gathers on Near, Mid and Far-offsets, to verify the credibility of the amplitude response in the prospect evaluation, through analyzing a case study of two exploratory wells; one has already penetrated a gas-bearing sandstone reservoir and the second one is dry sand, but drilled in two different prospects, using the AVO analysis, to understand the reservoir configuration and its relation to the different amplitude response. The results show that the missing of the short-offset data is the reason of the false anomaly encountered in the dry sand, due to some urban surface obstacles during acquiring the seismic data in the field, especially the study area is located in El Mansoura city, which it is a highly cultivated terrain, with multiple channels and many large orchards on the edge of the river, and sugar cane and rice fields. Several lessons have been learned, which how to differentiate between the gas reservoirs and non-reservoirs, by understanding the relation between the Near and Far-offset traces, to reduce the amplitude anomalies to their right justification, where missing of Near-offset data led to a pseudo-amplitude anomaly. The results led to a high success of exploration ratio as the positives vastly outweigh the negatives.

A new exploration tool for subtle stratigraphic traps in the offshore Nile Delta, Egypt

The offshore Nile Delta Basin is considered as one of the most promising hydrocarbon provinces in Egypt, with an excellent potential for gas and condensate reserves following future exploration. Most of the discoveries in this basin, such as the reservoirs of the Upper Miocene and the Middle–Upper Pliocene, have been enabled by the use of a direct hydrocarbon indicator (DHI), based on a class III seismic amplitude v. offset (AVO) anomaly. However, there are gas-bearing formations in the Lower Pliocene that have been successfully tested where the sand did not show any seismic amplitude anomaly in full stacks or in near- and far-offset sub-stacks. The AVO analysis of this sand reservoir is referred to as AVO class II-P. Another case of a subtle AVO class I anomaly in a Lower Pliocene gas reservoir has also been tested by three wells.These variations in AVO types push us to find a new methodology to reduce the risk of unsuccessful exploration wells, mainly using seismic data. The enhanced AVO pseudo-gradient attribute (EAP) has previously been used in other studies, mainly to highlight AVO class III anomalies. However, in the present paper, we demonstrate a workflow to identify all the principal AVO classes observed in this province. Computing the EAP attribute from our data, we find that AVO class I has negative EAP values, while the other classes have positive values. Class III and classes II and II-P may be distinguished from each other as the former yields a strong positive EAP value, whereas the latter two classes yield weak EAP responses.After determining the AVO class, we define and use a new model attribute, herein termed NM, to differentiate between gas- and water-bearing formations for each class of AVO anomaly found in this province. This new method was successfully tested in many areas in the Nile Delta Basin, where it has helped to identify subtle anomalies and thereby open the gate for further exploration activities in the area.

Imaging the Aquistore reservoir after 36 kilotonnes of CO2 injection using distributed acoustic sensing

Aquistore is a geologic [Formula: see text] storage project that is using a deep saline formation as a storage reservoir. From April 2015 to February 2016, approximately 36 kilotonnes of [Formula: see text] were injected into the reservoir at a depth of 3130–3350 m. We have developed an analysis of distributed acoustic sensing (DAS) 3D vertical seismic profiling data acquired in February 2016, marking the first seismic survey since injection began. The VSP data were processed in parallel with baseline preinjection data from a November 2013 survey, with the objective of detecting and characterizing the subsurface [Formula: see text] plume and evaluating the repeatability of DAS in a reservoir monitoring project. A single processing sequence was devised that (1) accurately imaged the reservoir for the baseline and monitor data and (2) attained adequate repeatability to observe time-lapse differences related to the presence of [Formula: see text]. Repeatability was somewhat compromised by the less advanced noise cancellation methodology of the DAS system used for the baseline survey. In the final cross-equalized migrated data volumes, normalized root-mean-square ([Formula: see text]rms) difference values of [Formula: see text] were attained at the reservoir level indicating good repeatability compared with most surface seismic studies. An injection-related amplitude anomaly with maximum [Formula: see text]rms values of approximately 0.7 is apparent in the Deadwood Formation of the reservoir, whereas no significant [Formula: see text]rms anomalies were observed near the injection and monitoring wells in the Black Island Member or above the reservoir.

Shallow Gas Prospect Evaluation in Shahbazpur Structure Using Seismic Attributes Analysis - a Case Study for Bhola Island, Southern Bangladesh

Shahbazpur structure is located in the southern Part of the central deep basin in the Hatia trough, where lie all the largest Gas fields of Bangladesh. A method is established to delineate the structural mapping precisely by interpreting four 2D seismic lines that are acquired over Shahbazpur structure. Moreover direct hydrocarbon indicators (DHI) related attributes are analyzed for further confirmation for presence of hydrocarbon. To do this synthetic seismogram generation, seismic to well tie, velocity modelling and depth conversion are performed. A limited number of seismic attributes functions that are available in an academic version of Petrel software are applied to analyze attributes. Seismic attribute analyses that are used in this interpretation mainly are associated to bright spot detection. Presence of bright spots or high amplitude anomaly over the present Shahbazpur structure, reservoir zone are observed. This signature will play a very important role in next well planning on the same structure to test the shallow accumulation of hydrocarbon. For better understanding of this shallow reserve, it is suggested to acquire 3D seismic data over Shahbazpur structure which will help to evaluate the hydrocarbon accumulation and to identify gas migration pathways. Dhaka Univ. J. Sci. 64(2): 135-140, 2016 (July)

Wavelet Basis Function Optimization and its Application in Carbonate Reservoir Fluid Detection

he purpose of this paper was to perform optimize the best wavelet basis function and TFA (Time frequency analysis) techniques on a target, in order to provide high-resolution instant spectrum data to help in the fluid detection. Wavelet transform is an effective tool to calculate the frequency. And spectral decomposition technique can depict the frequency characters of seismic reflection that are caused by fluid. In order to optimize the best wavelet basis function, different wavelet basis was tested on a sin model to determine the optimum parameters on the noised-sinusoidal model. Several wavelet bases were tested for the frequency recognition capability on the model, and then the optimum wavelet base function was used in the subset of the seismic data. The optimal wavelet basis was selected to test in the subset of the seismic data, strong amplitude anomaly showed. And so may be use the well-log interpretation result to guarantee that the strong amplitude anomaly have effects at the target.