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Collaborating Authors
Seismic processing and interpretation
Deciphering the Record of the Sun-Earth Dance in Well Logs: The Extra-Terrestrial Imprint and its Application to High-Resolution Stratigraphy and Well Correlation in South Furious Field, Offshore North Sabah
Gou, Patrick (SEA Hibiscus Sdn Bhd) | Raja Ismail, Raja Azlan (SEA Hibiscus Sdn Bhd) | Yuen, Florence (SEA Hibiscus Sdn Bhd) | Zulkifli, Nadia (SEA Hibiscus Sdn Bhd) | Hee, Randy Peter (SEA Hibiscus Sdn Bhd) | van der Vegt, Paul (PanTerra Geoconsultants) | Ralphie, Benard (Malaysia Petroleum Management, PETRONAS) | Hassan, Fazideen (Malaysia Petroleum Management, PETRONAS)
Abstract South Furious is an oilfield in the Inboard Belt offshore North Sabah with oil production since 1979. The field is heavily faulted and compartmentalized, making it structurally complex and challenging for development. It is believed that the field has a low recovery factor, despite having a relatively large oil in-place volume reported. Its highly-heterogenous Stage IVA reservoir with thin sand-shale intercalations, and poor seismic imaging quality make stratigraphic interpretation and well correlations highly uncertain. Recognizing the limitations of conventional methods for well correlation in South Furious, SEA Hibiscus decided to take a quantitative approach on the existing well logs itself, particularly the gamma ray (GR) curve. This data-driven approach is a shift from the unsuccessful model-based method. Cyclostratigraphic analysis using CycloLog works on the principle that extra-terrestrial forces described by the Milankovitch Cycles have a huge influence on sedimentation processes, and its record are preserved in the well logs that we acquire while drilling, although not always obvious without the proper quantitative approach. This high-resolution stratigraphic method allows the detection of cyclic signals in facies-sensitive wireline logs (e.g., gamma ray), including subtle ones, and at resolutions that are equivalent to 4th to 6th Order stratigraphic cycles. Utilizing the Integrated Prediction Error Filter Analysis (INPEFA), geological breaks or events are quantitatively and objectively identified. Cyclostratigraphic and climate stratigraphy concepts as described by Perlmutter and Matthews (1990) and Nio (2005) form the basis of this analysis, which is an evolution of traditional sequence stratigraphic concepts. Results from the 10 pilot wells in South Furious show dramatic improvements in the stratigraphic correlation resolution, particularly in the deeper/older sections, allowing correlations to be made across different fault block segments, previously nearly impossible. With the ongoing inclusion of more wells to the cyclostratigraphic study and future plans to integrate independent chemostratigraphic data, a more robust stratigraphic framework for the field would be established. Results from the current study prove that the cyclostratigraphic method allows objective, quantitative and data-driven stratigraphic well correlations to be made from a systematic and quantitative review of existing well logs, without additional rock sampling or measurement, and in a cost-effective manner. Geoscientists should always be receptive to new ways of working, including utilizing data and techniques that have origins outside mainstream geoscience.
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (0.88)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Challenges on Building Representative 3D Static Models under Subsurface Uncertainties for a Giant Carbonate Field in Central Luconia, Offshore Sarawak
Chongrueanglap, Pongsit (PTTEP HK) | Siriwattanakajorn, Warintaphat (PTTEP HK) | Hamdan, Mohamad Kamal bin (PTTEP) | Poret, Kelly La Grange (PTTEP) | Soontornnateepat, Thanutpong (PTTEP) | Mahamat, Sirichai (PTTEP) | Wongpaet, Khuananong (PTTEP) | Cheong, Yaw Peng (PTTEP)
Abstract This paper focuses on the challenges in building representative 3D static models under all subsurface uncertainties for a green field. The case study is based on a giant carbonate gas field, appraised with a few partially penetrated wells in Central Luconia province, offshore Sarawak, Malaysia. With very limited hard data for reservoir characterization, knowledge from Central Luconia literature and nearby field analogues had to be used together with the 3D seismic data. Standard geostatistical methodology was used to integrate the subsurface interpretations and to capture the identified subsurface uncertainties, i.e., structural framework, fluid contacts, facies distribution, petrophysical interpretations, saturation function, permeability prediction etc. Some of the key challenges, findings and results are listed below; How to quantify a long list of subsurface uncertainties with a manageable number of 3D static models? Full factorial design was used together with expert knowledge to limit the total number of uncertainties. How to quantify the structural uncertainty and the challenge in building geocellular grid for carbonate platform and pinnacle buildup? Even with very limited core data, the lithofacies interpretation was completed and incorporate 3D seismic data as representative 3D trend for distributing the expected carbonate facies. It is a massive challenge in characterizing the petrophysical properties for carbonate reservoirs, as heterogeneity (both primary and secondary processes) can be difficult to predict. Similar porosity seen in seismic inversion might have different flow behavior in permeability. Sub-seismic geological features like flooding surfaces might be acting as vertical baffles, which must be modelled as an important element of the geostatistical models. Reservoir characterization and uncertainty quantification will allow an improved understanding of the reservoir, and the results will guide the data acquisition program in subsequent appraisal campaign. This case study will enrich the knowledge within the Central Luconia carbonate province, and a discovery in a mature basin is still a massive challenge for reservoir characterization under uncertainties.
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (1.00)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment > Reef Environment (0.47)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition (0.95)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.35)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation > Evaluation of uncertainties (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- (2 more...)
Encapsulating Complex Carbonate Facie Heterogeneity into Static Reservoir Model through Seismic-Based Characterization, Lang-Lebah Field, Central Luconia, Offshore Sarawak
Suwannasri, Krongrath (PTTEP) | Yaw Peng, Cheong (PTTEP) | Asawachaisujja, Sirada (PTTEP) | Uttareun, Ratchadaporn (PTTEP) | Limpornpipat, Orapan (PTTEP) | Suphawajruksakul, Apichart (PTTEP) | Chongrueanglap, Pongsit (PTTEP)
Abstract Capturing the reservoir heterogeneity is crucial for optimizing field development. Lang-Lebah field is a Miocene carbonate platform with approximately 5 sq.km. in size and over 1 km in height with a high degree of heterogeneity in both vertical and horizontal directions. In this study, we conducted a seismic-based characterization to capture reservoir heterogeneity and then ran sequential gaussian simulation with a data from wells to build a static model for field development purpose. The method mainly comprises of four steps. The first step is to establish a relationship between reservoir properties (such as facie and porosity) to elastic properties (such as P- and S-wave impedances) to build conditional probability. The second step is running pre-stack inversion to derive P- and S-wave impedances as inputs for the third step. The posterior probability of each facie is determined through Bayesian classification using inverted impedances and the derived conditional probability as inputs. The last step is employing sequential gaussian simulation to build a static model using derived posterior probability of each facie and porosity cube. The static model encapsulates heterogeneity in terms of carbonate facie and reservoir properties. The observed heterogeneity is highly consistent with the understanding of geological model of this carbonate platform. The result shows lateral heterogeneity in each zone of high energy facies (such as reef margin) at the windward flank of the platform and low energy facies (such as lake) at platform interior. Thus, this result was elaborated for geological concept beyond the using well data alone. The result also shows a vertical succession from different carbonate reservoir deposit regarding to accommodation as carbonate build-out to a typical carbonate platform build-up continue to carbonate build-in. In addition, flooding event or surfaces, which is part of reservoir barrier, was also identified and included in this static model. The details of this successful novel study lay a fundamental work process for battling the challenge of gigantic carbonate characterization for field development. Because of this sophisticated model, we can properly plan the sequence of production and producing well targeting based on the derived reservoir heterogeneity resulting in enabling several Tscf of reserves and minimizing development costs.
- Geology > Sedimentary Geology > Depositional Environment (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.50)
- Geophysics > Seismic Surveying > Seismic Processing (0.48)
- Reservoir Description and Dynamics > Reservoir Simulation > Construction of static models (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
Abstract Stratigraphic forward modeling (SFM) is an innovative approach to subsurface facies prediction at the basin scale that augments and overcomes some of the limitations of conventional seismic, well, and analog data. As a multidisciplinary approach to play characterization, SFM improves the efficiency of current workflows, which is important given the current downward pressure on capex in oil and gas companies. A 2D SFM study on data from Browse basin, NW Australia, was conducted to enhance the prediction of facies distribution and improve play characterization by integrating SFM with other disciplines. The work started with seismic interpretation and depth conversion. Then, a third to fourth-order sequence stratigraphy interpretation was performed to determine the main sequence boundaries, maximum flooding surfaces, and a relative sea-level curve. The sequence stratigraphy results were later used to infer some of the inputs and parameters of the SFM model. The model simulates the deposition of clastic and carbonates from the Turonian (Late Cretaceous) to the present day. The results from the model were used to validate some of the geological concepts and the seismic interpretation. In addition, the approach enabled the prediction of reservoir quality, reservoir distribution, the presence of the seal, and the quantification of erosion. A 2D petroleum system model (PSM) covering the area from the Yampi shelf to the Seringapatam sub-basin was built using seismic interpretation, regional tectonic information, source rock geochemistry, and paleo heat flow. The results from SFM were integrated into a 2D PSM by resampling facies and erosion properties for each of the finely subdivided layers. The high-resolution 2D PSM with refined facies was simulated in geological time to model the basin evolution and its impact on all elements and processes of the petroleum system of Browse basin, which have been validated with nearby fields. As a result of this integrated approach, the risk of charge and entrapment in prospective stratigraphic traps was better understood and quantified. In addition, this approach helped to increase yet-to-find (YTF) hydrocarbon resources by accurately predicting reservoir distribution and extent. The generation of a 2D SFM and its integration within a multidisciplinary approach to predict facies represents a novel addition to exploration workflows. Adopting such an approach can improve significantly on the understanding of hydrocarbon entrapment and further reduce exploration risks.
- Oceania > Australia > Western Australia > North West Shelf (1.00)
- Oceania > Australia > Western Australia > Timor Sea (0.85)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (1.00)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (1.00)
- Geology > Geological Subdiscipline > Stratigraphy > Sequence Stratigraphy (0.92)
- Oceania > Australia > Western Australia > Western Australia > Timor Sea > Browse Basin (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Timor Sea > Browse Basin (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Browse Basin > Block WA-315-P > Plover Formation (0.99)
- (5 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Abstract This study presents a novel neural network model to explore its application in automatically interpreting subsurface faults from seismic images. A Wavelet Convolutional Neural Network (CNN) model that incorporates discrete wavelet decomposition is presented, and its capability in segmenting subsurface faults is analyzed. In this study, different neural network models are developed to compare their performance in segmenting subsurface faults. Sliced 2D seismic images are used as the input of the models. Pre-interpreted images with fault locations are used as the output of the models. Different CNN models are created using different pooling methods, including a traditional U-Net model with average pooling method, and an advanced Wavelet CNN model using wavelet pooling method. The results show that the Wavelet CNN model, which incorporates discrete wavelet transformation as the pooling layer, has the best performance comparing to traditional models in segmenting subsurface faults from input seismic images. It is more effective in saving edge features during pooling operations and outperforms the traditional U-Net model in segmenting subsurface faults from seismic images.
- Asia (0.69)
- North America > United States (0.47)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Neural networks (1.00)
Abstract Miocene carbonates have been producing gas in Central Luconia for more than 30 years (Warrlich et al., 2019). Approximately 65 TCF of recoverable gas have been discovered to date in these build-ups (Scherer, 1980; Mahmud and Saleh, 1999; Khazali et al., 2013; Kosa et al., 2015; Warrlich et al., 2019). One of the most recent carbonate discoveries in this region, Field X, is in its early-stage of reservoir characterization. Depositional and facies models have been created with newly acquired data from LL-C appraisal well. Tectonics, accommodation, and sea level contributed to the overall shape and deposition of the carbonate buildup. One appraisal well, LL-C was drilled and penetrated a thick carbonate section on the structure. With the available data, facies and conceptual depositional models were created using well logs, sidewall cores, conventional cores, cuttings, seismic, and an extensive literature review. At the time of this study, core laboratory analyses were not yet completed. The reservoir is separated into five zones based on well log, core, and seismic data. A precursory facies model was completed using only photographs from the sidewall cores acquired in all five zones of the structure and photographs from conventional core acquired in the upper reservoir interval. Five facies were identified: Coral, Packstone, Wackestone, Mudstone, and Cemented Margin. The data acquired in LL-C illustrates the complexity of carbonate reservoirs and the need to acquire core early in the appraisal of carbonate reservoirs.
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (1.00)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment > Reef Environment (0.75)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.52)
- Well Drilling > Drilling Operations > Coring, fishing (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Core analysis (1.00)
Abstract Deepwater fields are well known for their complex turbidite heterogeneity. J field, which has a water depth of 1600-1800 meters, is a distal deepwater turbidite fan located within a high compressional area, resulted in highly faulted structures. All wells drilled in the J field penetrated thin-bedded sand-shale reservoirs (average 30-80 cm) which are below current available toolsโ resolution. This has directly impacted the accuracy of reservoirs properties interpretation and characterization. Additionally, based on the acquired pressure data from past appraisal campaigns, the field is proven to be laterally and vertically compartmentalized. However, reservoir connectivity and producibility away from those appraisal wells remains uncertain and challenging to be identified, due to the legacy 3D seismic image quality, limitation in data resolutions, and limited regional data. This paper will briefly address the challenges of deepwater distal turbidites understanding while proposing a holistic workflow with the integration of 3D seismic and well data to enhance thin-bed interpretation and complex compartmentalization prediction.
- Geology > Structural Geology > Fault (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (1.00)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment > Deep Water Marine Environment (0.96)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Abstract Seismic forward modelling is typically done using the finite difference (FD) approach. However, this method suffers from numerical dispersion problems which translates into less focused stacks and a decrease in bandwidth coverage. To mitigate this problem, the pseudo analytical method formulated by Etgen and Brandersberg-Dahl in 2009 was utilized. This paper demonstrates that pseudo analyticsโ pseudo differential operator that utilizes velocity interpolation allows it to be more robust towards varying velocity and grid sizes while providing better amplitudes for shot gathers compared to the FD modelling scheme. FD and pseudo analytically generated gathers were then migrated using the reverse time migration (RTM) algorithm and showed that the pseudo analytically generated shot gathers were better at preserving shallower and higher frequency reflectors while at the same time better suppressed migration artifacts at the steeply dipping salt flank. The pseudo analytically generated gathers also provided an improved amplitude spectrum compared to FD especially in the lower frequency range of around 25-50 Hz. Various test cases demonstrate that the pseudo analytical method was shown to be a viable alternative to the typically used FD method in imaging at challenging geological environments such as salt.
- Geophysics > Seismic Surveying > Seismic Modeling (1.00)
- Geophysics > Seismic Surveying > Seismic Processing > Seismic Migration (0.55)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
Magnetometer Survey: Multi-Discipline Collaboration Impacting Bottom Line
Kamaruzaman, Muhd Akram (Sarawak Shell Berhad) | Din, Mohd Saifullah (Sarawak Shell Berhad) | Endot, Ernyza (Sarawak Shell Berhad) | Sim, Peter (Sarawak Shell Berhad) | Lojikim, Chrissie (Sarawak Shell Berhad) | Chang, Chung Yan (Sarawak Shell Berhad) | Mohd Ramli, Mohd Faiz (Sarawak Shell Berhad)
Abstract Central Luconia has been explored with hundreds of well since the 1950s. During that time, all offshore wells were drilled using hyperbolic positioning system which has lower accuracy compare to current satellite positioning system, which was only introduced in early 1990s. With this knowledge, the old exploration well's locations (which was drilled in 1970s) pose potential hazards in terms of seabed obstruction and potential well collision during the future development wells drilling. Without a reliable seismic to well tie, interpreter has difficulty in identifying the top of carbonate event for depth conversion, thus impacting the well delivery, static model building and subsurface reserves estimation. Onsite verification was carried out using a multibeam echosounder (MBES), a Side Scan Sonar (SSS), and a Sub Bottom Profiler (SBP) in accordance with standard site survey procedures, but the existing wellhead location was unable to be detected because the wells had been abandoned and cut off at the seabed level. Magnetometer was deployed to further investigate the existing wellhead location; the sensor was towed approximately about three (3) times water depth from the stern of the vessel and altitude 10m from the seabed. To navigate the towed sensor, Ultra Short Baseline (USBL) transponder was attached close to the sensor to get real time underwater positioning. Five (5) survey lines were designed centered at the suspected existing wellhead location with the coverage of 60m radius. During data acquisition, the magnetic anomalies were recorded in the system via receiver and total magnetic data was used for further analysis to derive the as-found wellhead location. During the interpretation, the area of ambient magnetic field distortion was identified and marked as anomaly which represents "area of suspected wellhead". The magnitude and pattern of such distortion was used for interpretation and combined with the coordinates from the positioning system (surface and underwater) onboard the survey vessel. The general total magnetic field reading is ranging between 40920nT and 41130nT with the magnetic anomaly/wellhead had magnetic value from 100nT to 115nT. The total magnetic field analytical signal value is ranging from 0 to 3.5. The target magnetic anomaly refers to the area with greatest analytical signal value where it is also the area with most drastic change of the total magnetic field. From the survey results, the as-found wellhead position varies from 48m - 53m compared to existing wellhead position. With the confirmation on the old wellhead location, this helps to derisk the well collisions study for future development well and also improves the seismic to well tie analysis to provide higher confidence in the Top Carbonate pick and a better inverted seismic match in the reservoir interval for properties distribution.
- Geophysics > Seismic Surveying > Seismic Interpretation > Well Tie (1.00)
- Geophysics > Magnetic Surveying (1.00)
Abstract Seismic-well tie is a crucial process to correlate subsurface information from well logs and acquired seismic data. Traditionally, a manual seismic-well tie is conducted based on the interpreter's visual pattern recognition, which is subjective, time-consuming, and may lead to unrealistic velocity distortion. This paper presents a new method to automatically tie seismic to well using Dynamic Time Warping (DTW) and Optimal Interpolation (OI), to save man-hour and to obtain a more reliable time-depth relationship. To produce a better tie, we use DTW to seek the appropriate amounts of time stretching and squeezing to match the synthetic and actual seismic. Then, we balance the rigid pattern matching of DTW by using OI to smooth DTW results and constrain changed rock velocity to be within physical bound. The invented technique has been used to tie seismic to six exploration wells in the Gulf of Thailand. The results from the automated method are then compared with the manual method. For all wells, resulting synthetic-seismic correlations from the automated well tie are higher than the manual method by 1.6%-14.9%. Applied time shifts from the automated and manual methods are then compared. Notably, time adjustment correlations between the automated and manual well tie are considerably high, around 72%-85%, suggesting that both methods yield similar outcomes, yet the automated well tie gives a slightly higher match between tied synthetic and observed seismic traces.
- Asia > Thailand (0.50)
- South America > Brazil > Bahia (0.45)
- North America > United States > Gulf of Mexico > Central GOM (0.24)