Integration of Impedance Inversion Results into the IRAP 3D Geomodel

SPE Asia Pacific Oil &Amp; Gas Conference and Exhibition

Xia

Cui

et al. 2014

Development of a coalbed methane (CBM) field in its early stage is often plagued by the lack of well control and scarcity of geological data over a large geographical area. Therefore, constructing a representative static model to estimate the in-place-volume presents a formidable challenge. In this paper we proposed a workflow to overcome this challenge and applied it to a CBM field in the northern Bowen Basin of Australia.This workflow may be considered as a best practice for the following reasons. First, it makes use of data from various sources including cores, well logs, seismic interpretation, and topography. Second, it performs rigorous quality control on these data, such as depth shift and log normalization. Third, coal ply division and correlation and subsequent structural modeling are based on three types of correlation: well-to-well, well-to-seismic and, well-seismic-Graphic Information System. Fourth, it establishes the low, base and high trends for the most important reservoir properties. Fifth, it constructs a base case static model by combining the aforementioned structural and reservoir property models. Sixth, it uses sensitivity analysis, which varies one reservoir parameter at one time, to rank the impact of reservoir parameters on in-place-volume. Seventh, it uses uncertainty analysis which varies all reservoir parameters simultaneously to arrive at the P10, P50 and P90 in-place-volumes and their corresponding static models which can then be used for reservoir simulations to estimate the recoverable volumes.

Section: Well-to-seismic Correlationmentioning

confidence: 99%

Best Practices in Static Modelling of a Coalbed Methane Field: An Example from the Bowen Basin in Australia

SPE Asia Pacific Oil &Amp; Gas Conference and Exhibition

Xia

Cui

et al. 2014

A Best Practice in Static Modeling of a Coalbed-Methane Field: An Example From the Bowen Basin in Australia

SPE Reservoir Evaluation &Amp; Engineering

Xia

Cui

et al. 2015

Summary The development of a coalbed-methane (CBM) field in its early stage is often plagued by the lack of well control and the scarcity of geological data across a large geographical area. Therefore, constructing a representative static model to estimate the in-place volume presents a formidable challenge. In this paper, we propose a work flow to overcome this challenge and apply it to a CBM field in the northern Bowen basin of Australia. One may consider this work flow as a best practice for the following reasons. First, it makes use of data from various sources including cores, well logs, seismic interpretation, and topography. Second, it performs rigorous quality control on these data, such as depth shift and log normalization. Third, coal-ply division and correlation and subsequent structural modeling are based on three types of correlation: well-to-well, well-to-seismic, and well-seismic-geographic information system. Fourth, it establishes the low, base, and high trends for the most-important reservoir properties. Fifth, it constructs a base-case static model by combining the aforementioned structural and reservoir-property models. Sixth, it uses sensitivity analysis, which varies one reservoir parameter at a time, to rank the impact of reservoir parameters on in-place volume. Seventh, it uses uncertainty analysis that varies all reservoir parameters simultaneously to arrive at the P10, P50, and P90 in-place volumes and their corresponding static models that one can use for reservoir simulations to estimate the recoverable volumes.

Inter-Well Sandstone Prediction and Facies Evolution by Multidisciplinary Integration: An Example from G Gas Field in Jabung Block in South Sumatra Basin

SPE/IATMI Asia Pacific Oil &Amp; Gas Conference and Exhibition

Ren

et al. 2015

In the development of conventional oil and gas projects, inter-well sandstone prediction and facies evolution provide benefit by reducing the number of wells drilled, optimizing well location and maximizing the performance of the wells. However, several particularly thorny issues were encountered in our study. Multi-bedded thin sandstone reservoirs were vertically stacked with thin coal seams. The main sedimentary facies of sandstones in areal and vertical directions varied quickly. This paper summarizes one multidisciplinary integration methodology to predict the distribution of inter- well sandstone and sedimentary facies in the South Sumatra Basin in Indonesia. To overcome the aforementioned disadvantages, this method included the following steps. First, it made use of multidisciplinary knowledge including mineralogy, sedimentology, lithology, geology, petrophysics and geophysics based on cores, well logs, and seismic data of various source data. Second, sequence strata division and correlation were studied with eleven target layers in order to describe this multi-stack reservoir. Then sedimentary facies system including braided channel and braided delta were identified based on reliable data from sedimentary structure of lithology, facies sequence, Formation Micro scanner Image data (FMI), and sedimentary characteristics of core samples such as: rock color, lithological features, mineral composition, and rock sedimentary structure. Fourth, a sandstone identification assessment standard was established to improve the precision of the reservoir prediction. Fifth, logging data and sedimentary facies were used to establish the facies log patterns. Favorable reservoir facies in strata were outlined based on the study of properties of sedimentary facies. Sixth, a four step procedure including seismic data partitioning, seismic attribute analysis, normalized seismic attributes of three compartments and sandstone thickness calculation was used to identify sandstone inter-well distribution. Seventh, multidisciplinary integration was used to understand facies and facies evolution to arrive at favourable facies and properties distribution which could then be used for geomodel building. This methodology constitutes a systematic and effective way to delineate the distribution of sandstones and sedimentary evolution for future well planning.