Sweet spots in the shale reservoirs of the Lower Silurian Longmaxi Formation in Weiyuan 201 Block of Sichuan Basin were predicted quantitatively using seismic data and fuzzy optimization method. First, based on seismic and rock physics analysis, the rock physics characteristics of the reservoirs were determined, and elastic parameters sensitive to shale reservoirs with high gas content were selected.
ZENG Qingcai1, CHEN Sheng1, 2, HE Pei1, YANG Qing1, GUO Xiaolong1, CHEN Peng1, DAI Chunmeng1, LI Xuan1, GAI Shaohua1, DENG Yu1, HOU Huaxing1
1.Research Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, China; 2.China University of Petroleum, Beijing 102249, China
Received date: 01 Aug. 2017; Revised date: 12 Apr. 2018.
Second, data volumes with high precision of the elastic parameters were obtained from pre-stack simultaneous inversion. The horizontal distribution of key parameters for shale gas evaluation were calculated based on the results of rock physics analysis. Then, the fuzzy evaluation equation was established by fuzzy optimization method with test and logging data of horizontal wells with similar operation conditions.
key parameters affecting the productivity of horizontal wells were sorted out and the weights of them in the sweet spots quantitative prediction were worked out by fuzzy optimization to set up a sweet spots evaluation system. Three classes of shale gas reservoirs which including two kinds of sweet spots were predicted with the above procedure, and the sweet spots have been predicted quantitatively by combining the above prediction results with the testing production. The testing results of 7 verification wells proved the reliability of the prediction results.
Shale gas refers to the unconventional natural gas accumulated in dark shale or carbon-rich shale and its interlayer in adsorbed or free state. Abundant shale gas resources are reported globally with low exploration and development degrees, and they have a significant potential for development. Statistics made by IEA (International Energy Agency) reveals that, the global unconventional natural gas reserves are far higher than conventional natural gas. Particularly, shale gas accounts for 63% of unconventional natural gas reserves and the global recoverable shale gas reserves reach up to 221×1012 m3.
Shale gas production has been increased considerably in recent years , owing to the breakthroughs made in horizontal drilling, volume fracturing and geophysical prediction techniques of sweet spots. As of 2016, about 20 shale gas provinces have been discovered in the U.S., and about 4447×108 m3 of shale gas was produced in 2016. Of these provinces, 7 are reported to have the annual shale gas production of over 200×108 m3. Compared with 2015, shale gas production in creased by 247×108 m3, or 5.5% in 2016. This trend continues and even tends to increase.
The success of shale gas development in the U.S. has triggered a revolution in the global shale gas domain. China has a huge amount of shale gas resources, and through years of exploration, has realized industrial exploitation of marine shale gas in the Sichuan Basin. However, no substantive break through has been made in other regions and domains. In general, China’s shale gas development has only just begun and remains in the technical preparation and industrial start-up stages.
China’s shale gas resources are distributed mainly in the Upper Ordovician Wufeng Formation – Lower Silurian Longmaxi Formation and the Cambrian Qiongzhusi Formation in the Sichuan Basin and adjoining areas, the South China. In comparison with the U.S. shale gas, China’s shale gas has the following features: old strata, high maturation, various factors that influence the high gas productivity and gas enrichment, and difficult prediction of seismic sweet spots. Researchers in China have carried out the study and application of seismic sweet spots prediction technology in shale gas exploration in the Jiaoshiba and other regions, and made some achievements.
However, these achievements are predominately based on qualitative prediction, with a few efforts of single parameter-based quantitative prediction[9–11]. Fuzzy optimization, as an integrated evaluation method, is based on fuzzy mathematics and applies the fundamental principle of fuzzy relation coupling to realize the quantification of the factors difficult to quantify that have multiple variables and fuzzy boundary.
This method is applicable to quantitative prediction of sweet spots in highly mature shale and similar complex issues. This paper, based on an example from the Upper Ordovician Wufeng Formation–Lower Silurian Long-maxi Formation in the Weiyuan Block, the Sichuan Basin, applies the fuzzy optimization method to predict the sweet spots zone in highly mature by seismic data quantitatively.
The Weiyuan shale gas field is located in the southwestern part of the Sichuan Basin, geographically in the Weiyuan County (Neijiang City), Zizhong County and Rong County (Zigong City), covering an overall area of 6 500 km2. Structurally, it lies in the Central Sichuan low & gentle uplift zone (Fig. 1).
Fig. 1. Location of the study area.
The Weiyuan block is a wide and gentle anticline. Within the block, the burial depth of the basal stratum of the Longmaxi Formation ranges from 1100 to 2800 m, which increases gradually from northwest to southeast (Fig. 2). The strata include, from the bottom to the top, the Pre-Cambrian metamorphic basement, the Sinian-Middle Triassic marine carbonate rock, and the Upper Triassic-Cretaceous clasolite rock. Two sets of high-quality shale are present in the Sinian-Middle Triassic strata: i.e., the Lower Cambrian Qiongzhusi Formation and the Lower Silurian Longmaxi Formation. This paper focuses on the Longmaxi Formation shale reservoirs in the Weiyuan 201 Block.
Fig. 2. Structural map of the base of the Longmaxi Formation in Block Weiyuan 201.
Based on lithology and well log features, the Longmaxi Formation can be divided into two members: i.e., Long-1 and Long-2 (Fig. 3). In the seismic profile, they are separated by an interface with strong amplitude and highly continuous peak reflection that can be traced over the whole area. Fig. 3 shows the lithology and conventional well logs of the Longmaxi Formation in Well Wei-201.
Fig. 3. Lithologic profile and conventional well logs of the Longmaxi Formation in Well Wei 201.
Well logs show that, the Long-1 member is funnel-shaped on GR, AC, DEN and Caliper logs, with the TOC exceeding 2%; the Long-2 member is bell-shaped on GR, AC, DEN and Caliper logs, with the TOC of less than 2%. The Long-1 member, the primary target for exploration in this region, is dominated by grey black calcareous shale and black shale interbedded with pyrite and calcareous bands, with more lamellations present in the bot- tom than in the middle-upper parts. In the Weiyuan area, the Long-1 member, with the thickness of 140 to 240 m (Fig. 3), is well preserved and regionally continuously distributed, and hence can be correlated over the whole region.
Geophysical response features of sweet spots
Features of the Longmaxi Formation shale gas reservoirs
Shale gas sweet spots refers to the reservoirs with moderate burial depth, high organic carbon content, high maturity, rich natural fractures, good preservation condition and high gas content, and likely to form complex fracture network after fracturing. Sweet spots distributed over a broad area form the sweet spots zone.
The “Technical Specification for Calculation and Evaluation of Shale Gas Resources/Reserves” (DZ/T 0254-2014) issued by the Ministry of Land and Resources states that, the parameters for shale gas reservoirs evaluation include 5 indexes: i.e., the effective shale thickness, total gas content, TOC, organic matter maturity (Ro) and brittle mineral content (Table 1)[15-16]. The spatial and horizontal distribution of the effective shale thickness, total gas content, TOC and brittle mineral content can be predicted using seismic data[17-18]. Production practice in the Weiyuan area suggests that, porosity and formation pressure have significant control on the distribution of sweet spots, and hence shall be included in the evaluation indexes.
Table 1. Parameters lower limit of gas-bearing shale reservoirs.
Under the standard framework discussed above, the reservoirs in the study area is divided into several sub-layers based on petrological, sedimentary structural, paleontological and electric data. The Long-1 member is divided into the Long-11 and Long-12 sub-members. The Long-11 sub-member is subdivided into the Long-111, Long-112, Long-113 and Long-114 sub-layers (Table 2).
Table 2. Features of sub-layers of the Long-11 sub-member of the Longmaxi Formation in Block Weiyuan 201.
Basis for quantitative prediction of sweet spots by seismic data
The shale gas development practice in the North America indicates that, shale’s TOC has significant control on total gas content of shale reservoirs. Therefore, TOC is considered as one of the most important index for shale reservoirs evaluation. Based on the standards of classification of shale reservoirs in China and the features of shale gas reservoirs in this area, shale gas reservoirs in our study area can be divided into three classes, depending primarily on the TOC content, and secondly on total gas content, effective porosity and brittle mineral content.
Class I reservoirs are the gas-rich shale with the TOC of no less than 3%, Class II reservoirs have the TOC content between 2% and 3% and Class III reservoirs are the ordinary shale with the TOC content less than 2%. Class I and Class II reservoirs, with the TOC content no less than 2%, are considered as the primary targets of shale gas development, that is the sweet spots. The classification standard is listed in Table 3.
Table 3. Standard of classification of shale gas reservoirs in the Changning and Weiyuan areas.
The results of the seismic rock physics analysis indicate that: (1) elastic parameters (e.g., Vp-Vs, density, impedance, Poisson’s ratio and Vp/Vs) of shale gas reservoirs decrease significantly as the TOC increases; (2) there is a sharp difference in the value of elastic parameters between the reservoirs (including Class I, II and III) and the surrounding rock (lime- stone), but overlap exists among different classes of reservoirs. Therefore, reservoirs can be distinguished from non reservoirs easily. But the quality of reservoirs can’t be predicted accurately. Fig. 4 shows the analysis of geophysical elastic parameters of shale gas reservoirs of the Longmaxi Formation and the limestone at its base from the wells in the study area.
Fig. 4. Seismic rock physics analysis of shale gas reservoirs.
The relationship between the TOC content and gas content varies in different maturity cases. Fig. 5a shows the relationship between the TOC and gas content of the Barnett shale in the U.S. Barnett shale, relatively lower in maturity, exhibits a fairly good linear positive correlation between the TOC content and gas content. It is therefore possible to compute its gas content directly with its TOC content. Fig. 5b shows the relationship of the TOC content and gas content of the study block.
Fig. 5. Relationship between TOC and gas content of shale gas reservoirs of different maturities.
The correlation between the TOC content and gas content is quite poor and, therefore, it is not possible to utilize TOC to quantitatively predict the high-quality gas-rich shale reservoirs.
Workflow and method to predict the sweet spots by seismic data
The first step was to perform the well log interpretation and seismic rock physics analysis on the basis of seismic data interpretation, and to study the rock physics characteristics of the shale reservoirs. The seismic elastic parameters that are sensitive to shale gas sweet spots were defined, and the quantitative relationships between the seismic elastic parameters and key parameters for sweet spots evaluation were established.
Then, pre-stack elastic parameter inversion was per formed by using well log and seismic data to acquire seismic elastic parameters, including the P-wave velocity, S-wave velocity and density. The elastic parameters were converted into reservoirs evaluation parameters based on the rock physics analysis results, to predict the spatial and horizontal distribution of TOC, reservoirs thickness, formation pressure and the content of brittle mineral. Lastly, the fuzzy optimization method was adopted for comprehensive prediction and evaluation of the sweet spots, to predict shale gas sweet spots quantitatively.
Pre-stack simultaneous inversión
Accurately prediction of key parameters, such as the thick ness of the reservoirs, the TOC content, porosity and brittle index, relies on pre-stack seismic inversion . Although pre-stack inversion technique has been applied broadly to reservoirs prediction in recent years, traditional pre-stack inversion is based primarily on partially stacked data volumes with strong anti-noise ability and good stability. However, the AVO information in original seismic pre-stack gather would be lost during the stacking process, leading to the low precision of elastic parameters from the inversion.