Understanding seismic resolution is critical when trying to build accurate reservoir models by integration of data coming from different disciplines. Lack of low frequencies in seismic data makes it band limited that limits its uses only for structural model but its availability and areal coverage suggests that it has valuable information to constrain the reservoir model. Increasing resolution to double through deterministic inversion can be achieved whereas additional constraints are needed to further increase this resolution. Thus, it is paramount to improve the resolution of seismic and detection of reservoir and be able to identify reservoir thickness and extension as accurately as possible in order to build reliable reservoir model. In this study, the uncertainty in seismic resolution versus detection and quantification of rock properties are investigated in terms of seismic inversion. The framework of improving seismic resolution presented in this study is based on integrating seismic and well data through seismic inversion. It considers reprocessing of seismic data for frequency enhancement, pre-conditioning, rock physics modelling, high quality well-to-seismic tie and wavelet extraction, low frequency modelling, stratigraphic grid definition, property proportion distribution, geostatistical variograms and lithology trends. A detailed method description is provided that has proven to have high stability. By using a series of simple examples it is demonstrated that understanding seismic resolution is challenging and significant efforts are needed to obtain a realistic reservoir image. Under careful control of the seismic wavelet characteristics including phase, frequency and amplitude; and provided the noise level of the seismic data is sufficiently low; useful information can be extracted from high resolution seismic inversion derivatives. It can serve the purpose of detecting beds much thinner than the conventionally accepted detection limit. The results reveal that high resolution seismic is not necessarily the data with high detectability. The novelty of this investigation is in the ability to improve seismic resolution and detection through robust deterministic and stochastic inversion to solve the most important problem on the ‘level of detail that one can see in seismic’. The observations made on real data leading to the idea of explaining seismic resolution and detection myth versus reality.
In the current age of declining oil prices, mature fields matter today more than ever. About 70% of the current world oil production is from mature fields. To unlock the remaining potential from these fields, new wells need to be implemented by utilising technological advancements in reservoir characterisation, well engineering and reservoir engineering. This paper focuses on improving reservoir understanding by using rock physics and seismic inversion technology on a mature field, which is located in offshore Sarawak Malaysia. Seismic data can be incorporated into an integrated workflow of predicting rock properties by utilising inversion processes that transform seismic data into a quantitative rock property, a descriptive measure of the reservoir. In this paper, an integrated workflow is adopted and it involves the application of rock physics driven seismic inversion for acoustic impedance (AI) prediction and geobody extraction. The extracted geobodies describe the areal extent of oil reservoir and changes in the rock property. The field being studied consists of multi-stacked channelised reservoirs containing substantial amount of crevasse splay sands. The main producing units are thin oil sands with initial gas caps. These reservoirs typically display a high degree of vertical and lateral heterogeneity. Seismic inversion and geobody prediction were used as a method for the prediction of petrophysical properties including porosity, Net-to-Gross (NTG), water saturation and permeability at geo-cellular scale. To this end, the information from different fault blocks was integrated for the simulation study and incorporated into the evaluation of the oil potential in this mature field. A holistic approach that comprises both a material balance study and a simulation study was adopted. The material balance study was used to verify the drive mechanism and to evaluate the transmissivity between different fault blocks. Prolific reservoirs were identified on inverted AI data and integrated into the static model for volumetric estimations and further high grading of the development drilling locations. As seismic inversion offers non-unique solutions, the integration of well log data allowed a technically acceptable answer as well as an estimation of the associated uncertainty. It can be concluded that rock physics driven seismic inversion results reduces uncertainty in property estimation during reservoir modelling while simultaneously improving field development plans. This paper focuses on how the integration of seismic and well data was used to optimally characterise an oil reservoir in a mature field development and create a fit-for- purpose reservoir model. The goal was to optimise reservoir characterisation and production management which leads to success and low risk re-development. Ultimately, the economics were improved through reducing the uncertainties in monetising the remaining by-passed oil reserves to a manageable range.
Reservoir pressure depletion and decline of production are two common features of many mature petroleum fields. Drilling and stimulation of long, highly-deviated wellbores is one of the many technologies commonly used to enhance the production in mature fields. Reservoir depletion results in reduction of in situ horizontal stresses and more specifically in the formation fracture gradient (FG). The presence of non-depleted and generally weak interbeds within the pressure depleted reservoirs with a low FG leads to a narrow drilling margin for new infill wells or laterals. Therefore, a robust knowledge of rock mechanical properties, formation pressures, the magnitude of in situ stresses and their evolution with production and depletion are essential for successful drilling of new wells in particular and the redevelopment of mature fields as a whole. A case study from a mature oil field in the Sarawak Basin, offshore Malaysia, is presented where the field geomechanical elements were constrained from field data acquired in more than 10 offset wells drilled in early 1980s, and a new re-development well drilled in 2014 with supplementary core, well logs and pressure data. The results of rock mechanical core tests along with acoustic logs in the new well were used to update and verify an early geomechanical model built in the area. Extensive production from more than 20 multi-layer sandstone reservoirs resulted in significant pressure depletion whilst some of the deeper and stronger reservoirs still contain significant oil reserves. The geomechanical model was used to identify the narrow-margin drilling and stability risks of infill deviated oil producers targeting by-passed oil in the deeper reservoirs, and horizontal water injectors planned to enhance oil recovery in the field. The results showed that both intermediate and production sections of planned wells would have narrow mud weight windows. Depending on the well trajectory, the production sections could have only 0.8 ppg drilling margin due to a higher depletion of deeper reservoirs. The analyses also highlighted thin, weak interbeds in the intermediate hole section that require a minimum mud weight of 10.0-10.5 ppg to limit shear failure to a manageable level considering hole cleaning challenges in high-angled wells whilst the FG of depleted sections could be as low as 11.3 ppg requiring stringent control on downhole pressure while drilling to keep the hole pressure within the safe margin. Optimum mud weights, safe drilling margins and casing setting points were determined for nine different well trajectories focusing on the azimuthal and inclination dependency of fracture and borehole collapse pressures. The subsequent drilling campaign of planned infill oil producers and water injectors in the field has been successful due to good drilling practices, using the recommended mud programs consistent with wellbore stability assessments, and careful bottomhole pressure control.
The success of extracting the best value from mature heterogeneous fields to meet global energy challenges is directly linked to innovation and creativity. The development of these fields requires optimized economic models and fit for purpose reservoir depletion strategies. Petroleum geoengineering is the answer to evaluating remaining opportunities and managing the key uncertainties using smart technologies and reducing the risk of development. This paper describes the field example of how a petroleum geoengineering based approach can optimize the fast track development of a marginal fault block within a complex oil field which is located in offshore Sarawak Malaysia. The advantages of this workflow compared to the conventional field development plan (FDP) approach is that the iterative time consumed in matching the dynamic model and adjusting the geological model has been properly managed. In our case study, this workflow has improved the quality of the technical proposal as well as saving project duration significantly. In accordance to the workflow, the reservoir architecture was interpreted based on seismic interpretation, geological and reservoir performance understanding. Seismic Inversion derived geobodies were then identified as development targets. Better delineation of the main geological features was achieved using a seismic inversion based algorithm. By prioritizing data consistency among geoscientists, geomodellers and reservoir engineers, a fast track field development plan was developed within manageable uncertainties. Greater reliability of inversion results help to avoid perpetuating bias tendencies on data used for model calibration or quality check. The petroleum geoengineering based study for such oil reservoir shows how an integrated approach enabled time saving for subsurface development concept identification covering range of estimated hydrocarbon volumes. As a result of geoengineering approach in marginal fault block, the technical proposal was completed within 8 months duration.
In oil & gas industry, it is evident that digitalization has become the leading technology to improve interactive data analysis in amultidisciplinary team. Exploitation of data has been a real challenge especially on mature fields with high real-time data frequency extraction on day to day basis. This paper aims to increasethe integration of data and workflow for building well models. An automated workflow through programming has been implemented in offshore Sarawak, Malaysia involving three (3) main processes, which are: procedures to use historical data to select IPR and VLP correlation for well models a workflow to predict well IPR using available surface data a built-in application to auto-match well models to selectthe most representative IPR model based onsufficient production data to be used in forecasting The well performance and technical potential of the field was evaluated in accordance to this workflow, resulting in significant time-saving when analysing the massive pool of data. This enables the proliferation of real-time data usage promptly. Employing this workflow minimizes misinterpretation of frequently ignored erroneous information compared to the conventional method. Greater reliability of well analysis using workflows helps to avoid perpetuating bias tendencies on data used for model calibration or quality check. This will result in better technical confidence needed to make decisions to move forward with development plans for a wide range of production rates and operating conditions. This paper will investigate the impact of using incorrect IPR or VLP versus the results of this workflow based on the same historical dataset. It will also demonstratehow the built-in automated process adds value in improving the understanding of well performance while ensuring that the models are calibrated to the entire historical data as accuratelyas possible.
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